Carlson, Eve B.; Palmieri, Patrick A.; Spain, David A.
2017-01-01
Objective We examined data from a prospective study of risk factors that increase vulnerability or resilience, exacerbate distress, or foster recovery to determine whether risk factors accurately predict which individuals will later have high posttraumatic (PT) symptom levels and whether brief measures of risk factors also accurately predict later symptom elevations. Method Using data from 129 adults exposed to traumatic injury of self or a loved one, we conducted receiver operating characteristic (ROC) analyses of 14 risk factors assessed by full-length measures, determined optimal cutoff scores and calculated predictive performance for the nine that were most predictive. For five risk factors, we identified sets of items that accounted for 90% of variance in total scores and calculated predictive performance for sets of brief risk measures. Results A set of nine risk factors assessed by full measures identified 89% of those who later had elevated PT symptoms (sensitivity) and 78% of those who did not (specificity). A set of four brief risk factor measures assessed soon after injury identified 86% of those who later had elevated PT symptoms and 72% of those who did not. Conclusions Use of sets of brief risk factor measures shows promise of accurate prediction of PT psychological disorder and probable PTSD or depression. Replication of predictive accuracy is needed in a new and larger sample. PMID:28622811
Michel, J-M; Willebois, S; Ribinik, P; Barrois, B; Colin, D; Passadori, Y
2012-10-01
An evaluation of predictive risk factors for pressure ulcers is essential in development of a preventive strategy on admission to hospitals and/or nursing homes. Identification of the predictive factors for pressure ulcers as of 2012. Systematic review of the literature querying the databases PASCAL Biomed, Cochrane Library and PubMed from 2000 through 2010. Immobility should be considered as a predictive risk factor for pressure ulcers (grade B). Undernutrition/malnutrition may also be a predictive risk factor for pressure ulcers (grade C). Even if the level of evidence is low, once these risk factors have been detected, management is essential. Sensitizing and mobilizing health care teams requires training in ways of tracking and screening. According to the experts, risk scales should be used. As decision aids, they should always be balanced and complemented by the clinical judgment of the treatment team. According to experts, it is important to know and predictively evaluate risk of pressure ulcers at the time of hospital admission. The predictive risk factors found in this study are identical to those highlighted at the 2001 consensus conference of which was PERSE was the promoter. Copyright © 2012. Published by Elsevier Masson SAS.
Terry, Dellara F; Pencina, Michael J; Vasan, Ramachandran S; Murabito, Joanne M; Wolf, Philip A; Hayes, Margaret Kelly; Levy, Daniel; D'Agostino, Ralph B; Benjamin, Emelia J
2005-11-01
To examine whether midlife cardiovascular risk factors predict survival and survival free of major comorbidities to the age of 85. Prospective community-based cohort study. Framingham Heart Study, Massachusetts. Two thousand five hundred thirty-one individuals (1,422 women) who attended at least two examinations between the ages of 40 and 50. Risk factors were classified at routine examinations performed between the ages of 40 and 50. Stepwise sex-adjusted logistic regression models predicting the outcomes of survival and survival free of morbidity to age 85 were selected from the following risk factors: systolic and diastolic blood pressure, total serum cholesterol, glucose intolerance, cigarette smoking, education, body mass index, physical activity index, pulse pressure, antihypertensive medication, and electrocardiographic left ventricular hypertrophy. More than one-third of the study sample survived to age 85, and 22% of the original study sample survived free of morbidity. Lower midlife blood pressure and total cholesterol levels, absence of glucose intolerance, nonsmoking status, higher educational attainment, and female sex predicted overall and morbidity-free survival. The predicted probability of survival to age 85 fell in the presence of accumulating risk factors: 37% for men with no risk factors to 2% with all five risk factors and 65% for women with no risk factors to 14% with all five risk factors. Lower levels of key cardiovascular risk factors in middle age predicted overall survival and major morbidity-free survival to age 85. Recognizing and modifying these factors may delay, if not prevent, age-related morbidity and mortality.
Mammographic density, breast cancer risk and risk prediction
Vachon, Celine M; van Gils, Carla H; Sellers, Thomas A; Ghosh, Karthik; Pruthi, Sandhya; Brandt, Kathleen R; Pankratz, V Shane
2007-01-01
In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models. PMID:18190724
Coronary heart disease risk stratification: pitfalls and possibilities.
Negi, Smita; Nambi, Vijay
Atherosclerosis of the coronary arteries, or coronary heart disease (CHD), is the most common cause of mortality in U.S. adults. The pathobiology of atherosclerosis and its complications is a continuum. At one end of the spectrum are young individuals without atherosclerotic disease who have not yet been exposed to lifestyle or other risk factors, and at the other end are patients with manifest atherosclerosis - myocardial infarction, stroke, and disabling peripheral arterial disease - where risk of recurrent disease and death is driven by the same factors initially responsible for the emergence of disease. However, it is clear that while risk factors are important in the development of CHD, not everyone with risk factors develops the disease and not everyone with CHD has risk factors. Furthermore, even similar degrees of exposure to a risk factor leads to disease in some individuals and not in others. Risk prediction, which is crucial in predicting and hence preventing disease, therefore becomes very challenging. In this article we review the currently available risk stratification tools for predicting CHD risk and discuss potential ways to improve risk prediction.
Sun, Jimeng; Hu, Jianying; Luo, Dijun; Markatou, Marianthi; Wang, Fei; Edabollahi, Shahram; Steinhubl, Steven E.; Daar, Zahra; Stewart, Walter F.
2012-01-01
Background: The ability to identify the risk factors related to an adverse condition, e.g., heart failures (HF) diagnosis, is very important for improving care quality and reducing cost. Existing approaches for risk factor identification are either knowledge driven (from guidelines or literatures) or data driven (from observational data). No existing method provides a model to effectively combine expert knowledge with data driven insight for risk factor identification. Methods: We present a systematic approach to enhance known knowledge-based risk factors with additional potential risk factors derived from data. The core of our approach is a sparse regression model with regularization terms that correspond to both knowledge and data driven risk factors. Results: The approach is validated using a large dataset containing 4,644 heart failure cases and 45,981 controls. The outpatient electronic health records (EHRs) for these patients include diagnosis, medication, lab results from 2003–2010. We demonstrate that the proposed method can identify complementary risk factors that are not in the existing known factors and can better predict the onset of HF. We quantitatively compare different sets of risk factors in the context of predicting onset of HF using the performance metric, the Area Under the ROC Curve (AUC). The combined risk factors between knowledge and data significantly outperform knowledge-based risk factors alone. Furthermore, those additional risk factors are confirmed to be clinically meaningful by a cardiologist. Conclusion: We present a systematic framework for combining knowledge and data driven insights for risk factor identification. We demonstrate the power of this framework in the context of predicting onset of HF, where our approach can successfully identify intuitive and predictive risk factors beyond a set of known HF risk factors. PMID:23304365
Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors.
Razavian, Narges; Blecker, Saul; Schmidt, Ann Marie; Smith-McLallen, Aaron; Nigam, Somesh; Sontag, David
2015-12-01
We present a new approach to population health, in which data-driven predictive models are learned for outcomes such as type 2 diabetes. Our approach enables risk assessment from readily available electronic claims data on large populations, without additional screening cost. Proposed model uncovers early and late-stage risk factors. Using administrative claims, pharmacy records, healthcare utilization, and laboratory results of 4.1 million individuals between 2005 and 2009, an initial set of 42,000 variables were derived that together describe the full health status and history of every individual. Machine learning was then used to methodically enhance predictive variable set and fit models predicting onset of type 2 diabetes in 2009-2011, 2010-2012, and 2011-2013. We compared the enhanced model with a parsimonious model consisting of known diabetes risk factors in a real-world environment, where missing values are common and prevalent. Furthermore, we analyzed novel and known risk factors emerging from the model at different age groups at different stages before the onset. Parsimonious model using 21 classic diabetes risk factors resulted in area under ROC curve (AUC) of 0.75 for diabetes prediction within a 2-year window following the baseline. The enhanced model increased the AUC to 0.80, with about 900 variables selected as predictive (p < 0.0001 for differences between AUCs). Similar improvements were observed for models predicting diabetes onset 1-3 years and 2-4 years after baseline. The enhanced model improved positive predictive value by at least 50% and identified novel surrogate risk factors for type 2 diabetes, such as chronic liver disease (odds ratio [OR] 3.71), high alanine aminotransferase (OR 2.26), esophageal reflux (OR 1.85), and history of acute bronchitis (OR 1.45). Liver risk factors emerge later in the process of diabetes development compared with obesity-related factors such as hypertension and high hemoglobin A1c. In conclusion, population-level risk prediction for type 2 diabetes using readily available administrative data is feasible and has better prediction performance than classical diabetes risk prediction algorithms on very large populations with missing data. The new model enables intervention allocation at national scale quickly and accurately and recovers potentially novel risk factors at different stages before the disease onset.
Hirase, Tatsuya; Inokuchi, Shigeru; Matsusaka, Nobuou; Nakahara, Kazumi; Okita, Minoru
2014-01-01
Developing a practical fall risk assessment tool to predict the occurrence of falls in the primary care setting is important because investigators have reported deterioration of physical function associated with falls. Researchers have used many performance tests to predict the occurrence of falls. These performance tests predict falls and also assess physical function and determine exercise interventions. However, the need for such specialists as physical therapists to accurately conduct these tests limits their use in the primary care setting. Questionnaires for fall prediction offer an easy way to identify high-risk fallers without requiring specialists. Using an existing fall assessment questionnaire, this study aimed to identify items specific to physical function and determine whether those items were able to predict falls and estimate physical function of high-risk fallers. The analysis consisted of both retrospective and prospective studies and used 2 different samples (retrospective, n = 1871; prospective, n = 292). The retrospective study and 3-month prospective study comprised community-dwelling individuals aged 65 years or older and older adults using community day centers. The number of falls, risk factors for falls (15 risk factors on the questionnaire), and physical function determined by chair standing test (CST) and Timed Up and Go Test (TUGT) were assessed. The retrospective study selected fall risk factors related to physical function. The prospective study investigated whether the number of selected risk factors could predict falls. The predictive power was determined using the area under the receiver operating characteristic curve. Seven of the 15 risk factors were related to physical function. The area under the receiver operating characteristic curve for the sum of the selected risk factors of previous falls plus the other risk factors was 0.82 (P = .00). The best cutoff point was 4 risk factors, with sensitivity and specificity of 84% and 68%, respectively. The mean values for the CST and TUGT at the best cutoff point were 12.9 and 12.5 seconds, respectively. In the retrospective study, the values for the CST and TUGT corresponding to the best cutoff point from the prospective study were 13.2 and 11.4 seconds, respectively. This study confirms that a screening tool comprising 7 fall risk factors can be used to predict falls. The values for the CST and TUGT corresponding to the best cutoff point for the selected 7 risk factors determined in our prospective study were similar to the cutoff points for the CST and TUGT in previous studies for fall prediction. We propose that the sum of the selected risk factors of previous falls plus the other risk factors may be identified as the estimated value for physical function. These findings may contribute to earlier identification of high-risk fallers and intervention for fall prevention.
Predictive and Prognostic Factors in Definition of Risk Groups in Endometrial Carcinoma
Sorbe, Bengt
2012-01-01
Background. The aim was to evaluate predictive and prognostic factors in a large consecutive series of endometrial carcinomas and to discuss pre- and postoperative risk groups based on these factors. Material and Methods. In a consecutive series of 4,543 endometrial carcinomas predictive and prognostic factors were analyzed with regard to recurrence rate and survival. The patients were treated with primary surgery and adjuvant radiotherapy. Two preoperative and three postoperative risk groups were defined. DNA ploidy was included in the definitions. Eight predictive or prognostic factors were used in multivariate analyses. Results. The overall recurrence rate of the complete series was 11.4%. Median time to relapse was 19.7 months. In a multivariate logistic regression analysis, FIGO grade, myometrial infiltration, and DNA ploidy were independent and statistically predictive factors with regard to recurrence rate. The 5-year overall survival rate was 73%. Tumor stage was the single most important factor with FIGO grade on the second place. DNA ploidy was also a significant prognostic factor. In the preoperative risk group definitions three factors were used: histology, FIGO grade, and DNA ploidy. Conclusions. DNA ploidy was an important and significant predictive and prognostic factor and should be used both in preoperative and postoperative risk group definitions. PMID:23209924
Online gaming and risks predict cyberbullying perpetration and victimization in adolescents.
Chang, Fong-Ching; Chiu, Chiung-Hui; Miao, Nae-Fang; Chen, Ping-Hung; Lee, Ching-Mei; Huang, Tzu-Fu; Pan, Yun-Chieh
2015-02-01
The present study examined factors associated with the emergence and cessation of youth cyberbullying and victimization in Taiwan. A total of 2,315 students from 26 high schools were assessed in the 10th grade, with follow-up performed in the 11th grade. Self-administered questionnaires were collected in 2010 and 2011. Multiple logistic regression was conducted to examine the factors. Multivariate analysis results indicated that higher levels of risk factors (online game use, exposure to violence in media, internet risk behaviors, cyber/school bullying experiences) in the 10th grade coupled with an increase in risk factors from grades 10 to 11 could be used to predict the emergence of cyberbullying perpetration/victimization. In contrast, lower levels of risk factors in the 10th grade and higher levels of protective factors coupled with a decrease in risk factors predicted the cessation of cyberbullying perpetration/victimization. Online game use, exposure to violence in media, Internet risk behaviors, and cyber/school bullying experiences can be used to predict the emergence and cessation of youth cyberbullying perpetration and victimization.
Family Factors Predicting Categories of Suicide Risk
ERIC Educational Resources Information Center
Randell, Brooke P.; Wang, Wen-Ling; Herting, Jerald R.; Eggert, Leona L.
2006-01-01
We compared family risk and protective factors among potential high school dropouts with and without suicide-risk behaviors (SRB) and examined the extent to which these factors predict categories of SRB. Subjects were randomly selected from among potential dropouts in 14 high schools. Based upon suicide-risk status, 1,083 potential high school…
Crooks, Denise; Tsui, Judith; Anderson, Bradley; Dossabhoy, Shernaz; Herman, Debra; Liebschutz, Jane M.; Stein, Michael D.
2016-01-01
Injection drug users (IDUs) are at increased risk of contracting HIV. From a clinical trial assessing an intervention to enhance the linkage of hospitalized patients to opioid treatment after discharge, we conducted multivariate analysis of baseline data from hospitalized IDUs with a history of opioid dependence (n = 104) to identify differences in factors predicting HIV drug and sex risk behaviors. Factors significantly associated with HIV drug risk were being non-Hispanic Caucasian and recent cocaine use. Being female, binge drinking, and poorer mental health were significantly associated with higher sex risk. Because factors predicting HIV sex risk behaviors differ from those predicting HIV drug risk, interventions aimed at specific HIV risks should have different behavioral and substance use targets. PMID:25063229
Tijssen, M J A; Van Os, J; Wittchen, H U; Lieb, R; Beesdo, K; Wichers, Marieke
2010-09-01
To examine factors increasing the risk for onset and persistence of subthreshold mania and depression. In a prospective cohort community study, the association between risk factors [a family history of mood disorders, trauma, substance use, attention-deficit/hyperactivity disorder (ADHD) and temperamental/personality traits] and onset of manic/depressive symptoms was determined in 705 adolescents. The interaction between baseline risk factors and baseline symptoms in predicting 8-year follow-up symptoms was used to model the impact of risk factors on persistence. Onset of manic symptoms was associated with cannabis use and novelty seeking (NS), but NS predicted a transitory course. Onset of depressive symptoms was associated with a family history of depression. ADHD and harm avoidance (HA) were associated with persistence of depressive symptoms, while trauma and a family history of depression predicted a transitory course. Different risk factors may operate during onset and persistence of subthreshold mania and depression. The differential associations found for mania and depression dimensions suggest partly different underlying mechanisms.
Rastrelli, Giulia; Corona, Giovanni; Fisher, Alessandra D; Silverii, Antonio; Mannucci, Edoardo; Maggi, Mario
2012-12-01
The classification of subjects as low or high cardiovascular (CV) risk is usually performed by risk engines, based upon multivariate prediction algorithms. However, their accuracy in predicting major adverse CV events (MACEs) is lower in high-risk populations as they take into account only conventional risk factors. To evaluate the accuracy of Progetto Cuore risk engine in predicting MACE in subjects with erectile dysfunction (ED) and to test the role of unconventional CV risk factors, specifically identified for ED. A consecutive series of 1,233 men (mean age 53.33 ± 9.08 years) attending our outpatient clinic for sexual dysfunction was longitudinally studied for a mean period of 4.4 ± 2.6 years. Several clinical, biochemical, and instrumental parameters were evaluated. Subjects were classified as high or low risk, according to previously reported ED-specific risk factors. In the overall population, Progetto Cuore-predicted population survival was not significantly different from the observed one (P = 0.545). Accordingly, receiver operating characteristic (ROC) analysis shows that Progetto Cuore has an accuracy of 0.697 ± 0.037 (P < 0.001) in predicting MACE. Considering subjects at high risk according to ED-specific risk factors, the observed incidence of MACE was significantly higher than the expected for both low educated and patients reporting partner's hypoactive sexual desire (HSD, both <0.05), but not for other described factors. The area under ROC curves of Progetto Cuore for MACE in subjects with low education and reported partner's HSD were 0.659 ± 0.053 (P = 0.008) and 0.550 ± 0.076 (P = 0.570), respectively. Overall, Progetto Cuore is a proper instrument for evaluating CV risk in ED subjects. However, in ED, other factors such as low education and partner's HSD concur to risk profile. At variance with low education, Progetto Cuore is not accurate enough to predict MACE in subjects with partner's HSD, suggesting that the latter effect is not mediated by conventional risk factors included in the algorithm. © 2012 International Society for Sexual Medicine.
Rodriguez, Christina M; Richardson, Michael J
2007-11-01
Progress in the child maltreatment field depends on refinements in leading models. This study examines aspects of social information processing theory (Milner, 2000) in predicting physical maltreatment risk in a community sample. Consistent with this theory, selected preexisting schema (external locus-of-control orientation, inappropriate developmental expectations, low empathic perspective-taking ability, and low perceived attachment relationship to child) were expected to predict child abuse risk beyond contextual factors (parenting stress and anger expression). Based on 115 parents' self-report, results from this study support cognitive factors that predict abuse risk (with locus of control, perceived attachment, or empathy predicting different abuse risk measures, but not developmental expectations), although the broad contextual factors involving negative affectivity and stress were consistent predictors across abuse risk markers. Findings are discussed with regard to implications for future model evaluations, with indications the model may apply to other forms of maltreatment, such as psychological maltreatment or neglect.
Rodriguez, Christina M.; Smith, Tamika L.; Silvia, Paul J.
2015-01-01
The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants’ own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. PMID:26631420
Rho, Mi Jung; Lee, Hyeseon; Lee, Taek-Ho; Cho, Hyun; Jung, Dong Jin; Kim, Dai-Jin; Choi, In Young
2017-12-27
Background : Understanding the risk factors associated with Internet gaming disorder (IGD) is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods : Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results : The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138), belief self-control (1.034), anxiety (1.086), pursuit of desired appetitive goals (1.105), money spent on gaming (1.005), weekday game time (1.081), offline community meeting attendance (2.060), and game community membership (1.393; p < 0.05 for all eight risk factors); Conclusions : These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment.
Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics
Lee, Hyeseon; Lee, Taek-Ho; Cho, Hyun; Kim, Dai-Jin; Choi, In Young
2017-01-01
Background: Understanding the risk factors associated with Internet gaming disorder (IGD) is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods: Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results: The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138), belief self-control (1.034), anxiety (1.086), pursuit of desired appetitive goals (1.105), money spent on gaming (1.005), weekday game time (1.081), offline community meeting attendance (2.060), and game community membership (1.393; p < 0.05 for all eight risk factors); Conclusions: These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment. PMID:29280953
Advances in the assessment and prediction of interpersonal violence.
Mills, Jeremy F
2005-02-01
This article underscores the weakness of clinical judgment as a mechanism for prediction with examples from other areas in the psychological literature. Clinical judgment has as its Achilles'heel the reliance on a person to incorporate multiple pieces of information while overcoming human judgment errors--a feat insurmountable thus far. The actuarial approach to risk assessment has overcome many of the weaknesses of clinical judgment and has been shown to be a much superior method. Nonetheless, the static/historical nature of the risk factors associated with most actuarial approaches is limiting. Advances in risk prediction will be found in part in the development of dynamic actuarial instruments that will measure both static/historical and changeable risk factors. The dynamic risk factors can be reevaluated on an ongoing basis, and it is proposed that the level of change in dynamic factors necessary to represent a significant change in overall risk will be an interactive function with static risk factors.
Sex similarities and differences in risk factors for recurrence of major depression.
van Loo, Hanna M; Aggen, Steven H; Gardner, Charles O; Kendler, Kenneth S
2017-11-27
Major depression (MD) occurs about twice as often in women as in men, but it is unclear whether sex differences subsist after disease onset. This study aims to elucidate potential sex differences in rates and risk factors for MD recurrence, in order to improve prediction of course of illness and understanding of its underlying mechanisms. We used prospective data from a general population sample (n = 653) that experienced a recent episode of MD. A diverse set of potential risk factors for recurrence of MD was analyzed using Cox models subject to elastic net regularization for males and females separately. Accuracy of the prediction models was tested in same-sex and opposite-sex test data. Additionally, interactions between sex and each of the risk factors were investigated to identify potential sex differences. Recurrence rates and the impact of most risk factors were similar for men and women. For both sexes, prediction models were highly multifactorial including risk factors such as comorbid anxiety, early traumas, and family history. Some subtle sex differences were detected: for men, prediction models included more risk factors concerning characteristics of the depressive episode and family history of MD and generalized anxiety, whereas for women, models included more risk factors concerning early and recent adverse life events and socioeconomic problems. No prominent sex differences in risk factors for recurrence of MD were found, potentially indicating similar disease maintaining mechanisms for both sexes. Course of MD is a multifactorial phenomenon for both males and females.
Memory Resilience to Alzheimer's Genetic Risk: Sex Effects in Predictor Profiles.
McDermott, Kirstie L; McFall, G Peggy; Andrews, Shea J; Anstey, Kaarin J; Dixon, Roger A
2017-10-01
Apolipoprotein E (APOE) ɛ4 and Clusterin (CLU) C alleles are risk factors for Alzheimer's disease (AD) and episodic memory (EM) decline. Memory resilience occurs when genetically at-risk adults perform at high and sustained levels. We investigated whether (a) memory resilience to AD genetic risk is predicted by biological and other risk markers and (b) the prediction profiles vary by sex and AD risk variant. Using a longitudinal sample of nondemented adults (n = 642, aged 53-95) we focused on memory resilience (over 9 years) to 2 AD risk variants (APOE, CLU). Growth mixture models classified resilience. Random forest analysis, stratified by sex, tested the predictive importance of 22 nongenetic risk factors from 5 domains (n = 24-112). For both sexes, younger age, higher education, stronger grip, and everyday novel cognitive activity predicted memory resilience. For women, 9 factors from functional, health, mobility, and lifestyle domains were also predictive. For men, only fewer depressive symptoms was an additional important predictor. The prediction profiles were similar for APOE and CLU. Although several factors predicted resilience in both sexes, a greater number applied only to women. Sex-specific mechanisms and intervention targets are implied. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Sun, Xiangqing; Elston, Robert C; Barnholtz-Sloan, Jill S; Falk, Gary W; Grady, William M; Faulx, Ashley; Mittal, Sumeet K; Canto, Marcia; Shaheen, Nicholas J; Wang, Jean S; Iyer, Prasad G; Abrams, Julian A; Tian, Ye D; Willis, Joseph E; Guda, Kishore; Markowitz, Sanford D; Chandar, Apoorva; Warfe, James M; Brock, Wendy; Chak, Amitabh
2016-05-01
Barrett's esophagus is often asymptomatic and only a small portion of Barrett's esophagus patients are currently diagnosed and under surveillance. Therefore, it is important to develop risk prediction models to identify high-risk individuals with Barrett's esophagus. Familial aggregation of Barrett's esophagus and esophageal adenocarcinoma, and the increased risk of esophageal adenocarcinoma for individuals with a family history, raise the necessity of including genetic factors in the prediction model. Methods to determine risk prediction models using both risk covariates and ascertained family data are not well developed. We developed a Barrett's Esophagus Translational Research Network (BETRNet) risk prediction model from 787 singly ascertained Barrett's esophagus pedigrees and 92 multiplex Barrett's esophagus pedigrees, fitting a multivariate logistic model that incorporates family history and clinical risk factors. The eight risk factors, age, sex, education level, parental status, smoking, heartburn frequency, regurgitation frequency, and use of acid suppressant, were included in the model. The prediction accuracy was evaluated on the training dataset and an independent validation dataset of 643 multiplex Barrett's esophagus pedigrees. Our results indicate family information helps to predict Barrett's esophagus risk, and predicting in families improves both prediction calibration and discrimination accuracy. Our model can predict Barrett's esophagus risk for anyone with family members known to have, or not have, had Barrett's esophagus. It can predict risk for unrelated individuals without knowing any relatives' information. Our prediction model will shed light on effectively identifying high-risk individuals for Barrett's esophagus screening and surveillance, consequently allowing intervention at an early stage, and reducing mortality from esophageal adenocarcinoma. Cancer Epidemiol Biomarkers Prev; 25(5); 727-35. ©2016 AACR. ©2016 American Association for Cancer Research.
Risk factors for Apgar score using artificial neural networks.
Ibrahim, Doaa; Frize, Monique; Walker, Robin C
2006-01-01
Artificial Neural Networks (ANNs) have been used in identifying the risk factors for many medical outcomes. In this paper, the risk factors for low Apgar score are introduced. This is the first time, to our knowledge, that the ANNs are used for Apgar score prediction. The medical domain of interest used is the perinatal database provided by the Perinatal Partnership Program of Eastern and Southeastern Ontario (PPPESO). The ability of the feed forward back propagation ANNs to generate strong predictive model with the most influential variables is tested. Finally, minimal sets of variables (risk factors) that are important in predicting Apgar score outcome without degrading the ANN performance are identified.
Jones, Damon E; Feinberg, Mark E; Cleveland, Michael J; Cooper, Brittany Rhoades
2012-11-01
We examined the independent and combined influence of major risk and protective factors on youths' alcohol use. Five large data sets provided similar measures of alcohol use and risk or protective factors. We carried out analyses within each data set, separately for boys and girls in 8th and 10th grades. We included interaction and curvilinear predictive terms in final models if results were robust across data sets. We combined results using meta-analytic techniques. Individual, family, and peer risk factors and a community protective factor moderately predicted youths' alcohol use. Family and school protective factors did not predict alcohol use when combined with other factors. Youths' antisocial attitudes were more strongly associated with alcohol use for those also reporting higher levels of peer or community risk. For certain risk factors, the association with alcohol use varied across different risk levels. Efforts toward reducing youths' alcohol use should be based on robust estimates of the relative influence of risk and protective factors across adolescent environment domains. Public health advocates should focus on context (e.g., community factors) as a strategy for curbing underage alcohol use.
Identifying the necessary and sufficient number of risk factors for predicting academic failure.
Lucio, Robert; Hunt, Elizabeth; Bornovalova, Marina
2012-03-01
Identifying the point at which individuals become at risk for academic failure (grade point average [GPA] < 2.0) involves an understanding of which and how many factors contribute to poor outcomes. School-related factors appear to be among the many factors that significantly impact academic success or failure. This study focused on 12 school-related factors. Using a thorough 5-step process, we identified which unique risk factors place one at risk for academic failure. Academic engagement, academic expectations, academic self-efficacy, homework completion, school relevance, school safety, teacher relationships (positive relationship), grade retention, school mobility, and school misbehaviors (negative relationship) were uniquely related to GPA even after controlling for all relevant covariates. Next, a receiver operating characteristic curve was used to determine a cutoff point for determining how many risk factors predict academic failure (GPA < 2.0). Results yielded a cutoff point of 2 risk factors for predicting academic failure, which provides a way for early identification of individuals who are at risk. Further implications of these findings are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.
Predicting risk for childhood asthma by pre-pregnancy, perinatal, and postnatal factors.
Wen, Hui-Ju; Chiang, Tung-Liang; Lin, Shio-Jean; Guo, Yue Leon
2015-05-01
Symptoms of atopic disease start early in human life. Predicting risk for childhood asthma by early-life exposure would contribute to disease prevention. A birth cohort study was conducted to investigate early-life risk factors for childhood asthma and to develop a predictive model for the development of asthma. National representative samples of newborn babies were obtained by multistage stratified systematic sampling from the 2005 Taiwan Birth Registry. Information on potential risk factors and children's health was collected by home interview when babies were 6 months old and 5 yr old, respectively. Backward stepwise regression analysis was used to identify the risk factors of childhood asthma for predictive models that were used to calculate the probability of childhood asthma. A total of 19,192 children completed the study satisfactorily. Physician-diagnosed asthma was reported in 6.6% of 5-yr-old children. Pre-pregnancy factors (parental atopy and socioeconomic status), perinatal factors (place of residence, exposure to indoor mold and painting/renovations during pregnancy), and postnatal factors (maternal postpartum depression and the presence of atopic dermatitis before 6 months of age) were chosen for the predictive models, and the highest predicted probability of asthma in 5-yr-old children was 68.1% in boys and 78.1% in girls; the lowest probability in boys and girls was 4.1% and 3.2%, respectively. This investigation provides a technique for predicting risk of childhood asthma that can be used to developing a preventive strategy against asthma. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Recent development of risk-prediction models for incident hypertension: An updated systematic review
Xiao, Lei; Liu, Ya; Wang, Zuoguang; Li, Chuang; Jin, Yongxin; Zhao, Qiong
2017-01-01
Background Hypertension is a leading global health threat and a major cardiovascular disease. Since clinical interventions are effective in delaying the disease progression from prehypertension to hypertension, diagnostic prediction models to identify patient populations at high risk for hypertension are imperative. Methods Both PubMed and Embase databases were searched for eligible reports of either prediction models or risk scores of hypertension. The study data were collected, including risk factors, statistic methods, characteristics of study design and participants, performance measurement, etc. Results From the searched literature, 26 studies reporting 48 prediction models were selected. Among them, 20 reports studied the established models using traditional risk factors, such as body mass index (BMI), age, smoking, blood pressure (BP) level, parental history of hypertension, and biochemical factors, whereas 6 reports used genetic risk score (GRS) as the prediction factor. AUC ranged from 0.64 to 0.97, and C-statistic ranged from 60% to 90%. Conclusions The traditional models are still the predominant risk prediction models for hypertension, but recently, more models have begun to incorporate genetic factors as part of their model predictors. However, these genetic predictors need to be well selected. The current reported models have acceptable to good discrimination and calibration ability, but whether the models can be applied in clinical practice still needs more validation and adjustment. PMID:29084293
Inability to predict postpartum hemorrhage: insights from Egyptian intervention data
2011-01-01
Background Knowledge on how well we can predict primary postpartum hemorrhage (PPH) can help policy makers and health providers design current delivery protocols and PPH case management. The purpose of this paper is to identify risk factors and determine predictive probabilities of those risk factors for primary PPH among women expecting singleton vaginal deliveries in Egypt. Methods From a prospective cohort study, 2510 pregnant women were recruited over a six-month period in Egypt in 2004. PPH was defined as blood loss ≥ 500 ml. Measures of blood loss were made every 20 minutes for the first 4 hours after delivery using a calibrated under the buttocks drape. Using all variables available in the patients' charts, we divided them in ante-partum and intra-partum factors. We employed logistic regression to analyze socio-demographic, medical and past obstetric history, and labor and delivery outcomes as potential PPH risk factors. Post-model predicted probabilities were estimated using the identified risk factors. Results We found a total of 93 cases of primary PPH. In multivariate models, ante-partum hemoglobin, history of previous PPH, labor augmentation and prolonged labor were significantly associated with PPH. Post model probability estimates showed that even among women with three or more risk factors, PPH could only be predicted in 10% of the cases. Conclusions The predictive probability of ante-partum and intra-partum risk factors for PPH is very low. Prevention of PPH to all women is highly recommended. PMID:22123123
ERIC Educational Resources Information Center
Chen, Ji-Kang; Astor, Ron Avi
2010-01-01
The current study explores whether theorized risk factors in Western countries can be used to predict school violence perpetration in an Asian cultural context. The study examines the associations between risk factors and school violence perpetration in Taiwan. Data were obtained from a nationally representative sample of 14,022 students from…
Ho, Chih-I; Chen, Jau-Yuan; Chen, Shou-Yen; Tsai, Yi-Wen; Weng, Yi-Ming; Tsao, Yu-Chung; Li, Wen-Cheng
2015-10-01
The triglycerides-to-high-density lipoprotein-cholesterol (TG/HDL-C) ratio has been identified as a biomarker of insulin resistance and a predictor for atherosclerosis. The objectives of this study were to investigate which the TG/HDL-C ratio is useful to detect metabolic syndrome (MS) risk factors and subclinical chronic kidney disease (CKD) in general population without known CKD or renal impairment and to compare predictive accuracy of MS risk factors. This was a cross-sectional study. A total 46,255 subjects aged ≥18 years undergoing health examination during 2010-2011 in Taiwan. The independent associations between TG/HDL-C ratio quartiles, waist circumstance (WC) waist-to-height ratio (WHtR), mean atrial pressure (MAP), and CKD prevalence was analyzed by using logistic regression models. Analyses of the areas under receiver operating characteristic (ROC) were performed to determine the accuracy of MS risk factors in predicting CKD. A dose-response manner was observed for the prevalence of CKD and measurements of MS risk factors, showing increases from the lowest to the highest quartile of the TG/HDL-C ratio. Males and females in the highest TG/HDL-C ratio quartile (>2.76) had a 1.4-fold and 1.74-fold greater risk of CKD than those in the lowest quartile (≤1.04), independent of confounding factors. Mean arterial pressure (MAP) had the highest AUC for predicting CKD among MS risk factors. The TG/HDL-C ratio was an independent risk factor for CKD, but it showed no superiority over MAP in predicting CKD. A TG/HDL-C ratio ≥2.76 may be useful in clinical practice to detect subjects with worsened cardiometabolic profile who need monitoring to prevent CKD. TG/HDL-C ratio is an independent risk factor for CKD in adults aged 18-50 years. MAP was the most powerful predictor over other MS risk factors in predicting CKD. However, longitudinal and comparative studies are required to demonstrate the predictive value of TG/HDL-C on the onset and progression of CKD over time. Copyright © 2014 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Predictive Modeling of Risk Factors and Complications of Cataract Surgery
Gaskin, Gregory L; Pershing, Suzann; Cole, Tyler S; Shah, Nigam H
2016-01-01
Purpose To quantify the relationship between aggregated preoperative risk factors and cataract surgery complications, as well as to build a model predicting outcomes on an individual-level—given a constellation of demographic, baseline, preoperative, and intraoperative patient characteristics. Setting Stanford Hospital and Clinics between 1994 and 2013. Design Retrospective cohort study Methods Patients age 40 or older who received cataract surgery between 1994 and 2013. Risk factors, complications, and demographic information were extracted from the Electronic Health Record (EHR), based on International Classification of Diseases, 9th edition (ICD-9) codes, Current Procedural Terminology (CPT) codes, drug prescription information, and text data mining using natural language processing. We used a bootstrapped least absolute shrinkage and selection operator (LASSO) model to identify highly-predictive variables. We built random forest classifiers for each complication to create predictive models. Results Our data corroborated existing literature on postoperative complications—including the association of intraoperative complications, complex cataract surgery, black race, and/or prior eye surgery with an increased risk of any postoperative complications. We also found a number of other, less well-described risk factors, including systemic diabetes mellitus, young age (<60 years old), and hyperopia as risk factors for complex cataract surgery and intra- and post-operative complications. Our predictive models based on aggregated outperformed existing published models. Conclusions The constellations of risk factors and complications described here can guide new avenues of research and provide specific, personalized risk assessment for a patient considering cataract surgery. The predictive capacity of our models can enable risk stratification of patients, which has utility as a teaching tool as well as informing quality/value-based reimbursements. PMID:26692059
Rodriguez, Christina M; Smith, Tamika L; Silvia, Paul J
2016-01-01
The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants' own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. Copyright © 2015 Elsevier Ltd. All rights reserved.
Wang, X-M; Yin, S-H; Du, J; Du, M-L; Wang, P-Y; Wu, J; Horbinski, C M; Wu, M-J; Zheng, H-Q; Xu, X-Q; Shu, W; Zhang, Y-J
2017-07-01
Retreatment of tuberculosis (TB) often fails in China, yet the risk factors associated with the failure remain unclear. To identify risk factors for the treatment failure of retreated pulmonary tuberculosis (PTB) patients, we analyzed the data of 395 retreated PTB patients who received retreatment between July 2009 and July 2011 in China. PTB patients were categorized into 'success' and 'failure' groups by their treatment outcome. Univariable and multivariable logistic regression were used to evaluate the association between treatment outcome and socio-demographic as well as clinical factors. We also created an optimized risk score model to evaluate the predictive values of these risk factors on treatment failure. Of 395 patients, 99 (25·1%) were diagnosed as retreatment failure. Our results showed that risk factors associated with treatment failure included drug resistance, low education level, low body mass index (6 months), standard treatment regimen, retreatment type, positive culture result after 2 months of treatment, and the place where the first medicine was taken. An Optimized Framingham risk model was then used to calculate the risk scores of these factors. Place where first medicine was taken (temporary living places) received a score of 6, which was highest among all the factors. The predicted probability of treatment failure increases as risk score increases. Ten out of 359 patients had a risk score >9, which corresponded to an estimated probability of treatment failure >70%. In conclusion, we have identified multiple clinical and socio-demographic factors that are associated with treatment failure of retreated PTB patients. We also created an optimized risk score model that was effective in predicting the retreatment failure. These results provide novel insights for the prognosis and improvement of treatment for retreated PTB patients.
Dong, Wen; Yang, Kun; Xu, Quan-Li; Yang, Yu-Lian
2015-01-01
This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9) human infections: the spatial-temporal factor φ (OR = 2546669.382, p < 0.001), migration route (OR = 0.993, p < 0.01), river (OR = 0.861, p < 0.001), lake(OR = 0.992, p < 0.001), road (OR = 0.906, p < 0.001), railway (OR = 0.980, p < 0.001), temperature (OR = 1.170, p < 0.01), precipitation (OR = 0.615, p < 0.001) and relative humidity (OR = 1.337, p < 0.001). The improved model obtained a better prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101) of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70) of the predictive risk map, whereas 44.6% (45/101) of which overlaid on the high risk areas (the predictive risk > 0.70) for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%). The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9) human infections in February 2014. These results provided baseline data for the control and prevention of future human infections. PMID:26633446
Assessing suicide risk among callers to crisis hotlines: a confirmatory factor analysis.
Witte, Tracy K; Gould, Madelyn S; Munfakh, Jimmie Lou Harris; Kleinman, Marjorie; Joiner, Thomas E; Kalafat, John
2010-09-01
Our goal was to investigate the factor structure of a risk assessment tool utilized by suicide hotlines and to determine the predictive validity of the obtained factors in predicting subsequent suicidal behavior. We conducted an Exploratory Factor Analysis (EFA), an EFA in a Confirmatory Factor Analysis (EFA/CFA) framework, and a CFA on independent subsamples derived from a total sample of 1,085. Similar to previous studies, we found consistent evidence for a two-factor solution, with one factor representing a more pernicious form of suicide risk (i.e., Resolved Plans and Preparations; RPP) and one factor representing milder suicidal ideation (i.e., Suicidal Desire and Ideation; SDI). The RPP factor trended toward being more predictive of suicidal ideation at follow-up than the SDI factor. (c) 2010 Wiley Periodicals, Inc.
Quantifying prognosis with risk predictions.
Pace, Nathan L; Eberhart, Leopold H J; Kranke, Peter R
2012-01-01
Prognosis is a forecast, based on present observations in a patient, of their probable outcome from disease, surgery and so on. Research methods for the development of risk probabilities may not be familiar to some anaesthesiologists. We briefly describe methods for identifying risk factors and risk scores. A probability prediction rule assigns a risk probability to a patient for the occurrence of a specific event. Probability reflects the continuum between absolute certainty (Pi = 1) and certified impossibility (Pi = 0). Biomarkers and clinical covariates that modify risk are known as risk factors. The Pi as modified by risk factors can be estimated by identifying the risk factors and their weighting; these are usually obtained by stepwise logistic regression. The accuracy of probabilistic predictors can be separated into the concepts of 'overall performance', 'discrimination' and 'calibration'. Overall performance is the mathematical distance between predictions and outcomes. Discrimination is the ability of the predictor to rank order observations with different outcomes. Calibration is the correctness of prediction probabilities on an absolute scale. Statistical methods include the Brier score, coefficient of determination (Nagelkerke R2), C-statistic and regression calibration. External validation is the comparison of the actual outcomes to the predicted outcomes in a new and independent patient sample. External validation uses the statistical methods of overall performance, discrimination and calibration and is uniformly recommended before acceptance of the prediction model. Evidence from randomised controlled clinical trials should be obtained to show the effectiveness of risk scores for altering patient management and patient outcomes.
Prediction and Informative Risk Factor Selection of Bone Diseases.
Li, Hui; Li, Xiaoyi; Ramanathan, Murali; Zhang, Aidong
2015-01-01
With the booming of healthcare industry and the overwhelming amount of electronic health records (EHRs) shared by healthcare institutions and practitioners, we take advantage of EHR data to develop an effective disease risk management model that not only models the progression of the disease, but also predicts the risk of the disease for early disease control or prevention. Existing models for answering these questions usually fall into two categories: the expert knowledge based model or the handcrafted feature set based model. To fully utilize the whole EHR data, we will build a framework to construct an integrated representation of features from all available risk factors in the EHR data and use these integrated features to effectively predict osteoporosis and bone fractures. We will also develop a framework for informative risk factor selection of bone diseases. A pair of models for two contrast cohorts (e.g., diseased patients versus non-diseased patients) will be established to discriminate their characteristics and find the most informative risk factors. Several empirical results on a real bone disease data set show that the proposed framework can successfully predict bone diseases and select informative risk factors that are beneficial and useful to guide clinical decisions.
Macleod, John; Metcalfe, Chris; Smith, George Davey; Hart, Carole
2007-09-01
To assess the value of psychosocial risk factors in discriminating between individuals at higher and lower risk of coronary heart disease, using risk prediction equations. Prospective observational study. Scotland. 5191 employed men aged 35 to 64 years and free of coronary heart disease at study enrollment Area under receiver operating characteristic (ROC) curves for risk prediction equations including different risk factors for coronary heart disease. During the first 10 years of follow up, 203 men died of coronary heart disease and a further 200 were admitted to hospital with this diagnosis. Area under the ROC curve for the standard Framingham coronary risk factors was 74.5%. Addition of "vital exhaustion" and psychological stress led to areas under the ROC curve of 74.5% and 74.6%, respectively. Addition of current social class and lifetime social class to the standard Framingham equation gave areas under the ROC curve of 74.6% and 74.9%, respectively. In no case was there strong evidence for improved discrimination of the model containing the novel risk factor over the standard model. Consideration of psychosocial risk factors, including those that are strong independent predictors of heart disease, does not substantially influence the ability of risk prediction tools to discriminate between individuals at higher and lower risk of coronary heart disease.
Chao, Tze-Fan; Lip, Gregory Y H; Lin, Yenn-Jiang; Chang, Shih-Lin; Lo, Li-Wei; Hu, Yu-Feng; Tuan, Ta-Chuan; Liao, Jo-Nan; Chung, Fa-Po; Chen, Tzeng-Ji; Chen, Shih-Ann
2018-03-01
While modifiable bleeding risks should be addressed in all patients with atrial fibrillation (AF), use of a bleeding risk score enables clinicians to 'flag up' those at risk of bleeding for more regular patient contact reviews. We compared a risk assessment strategy for major bleeding and intracranial hemorrhage (ICH) based on modifiable bleeding risk factors (referred to as a 'MBR factors' score) against established bleeding risk stratification scores (HEMORR 2 HAGES, HAS-BLED, ATRIA, ORBIT). A nationwide cohort study of 40,450 AF patients who received warfarin for stroke prevention was performed. The clinical endpoints included ICH and major bleeding. Bleeding scores were compared using receiver operating characteristic (ROC) curves (areas under the ROC curves [AUCs], or c-index) and the net reclassification index (NRI). During a follow up of 4.60±3.62years, 1581 (3.91%) patients sustained ICH and 6889 (17.03%) patients sustained major bleeding events. All tested bleeding risk scores at baseline were higher in those sustaining major bleeds. When compared to no ICH, patients sustaining ICH had higher baseline HEMORR 2 HAGES (p=0.003), HAS-BLED (p<0.001) and MBR factors score (p=0.013) but not ATRIA and ORBIT scores. When HAS-BLED was compared to other bleeding scores, c-indexes were significantly higher compared to MBR factors (p<0.001) and ORBIT (p=0.05) scores for major bleeding. C-indexes for the MBR factors score was significantly lower compared to all other scores (De long test, all p<0.001). When NRI was performed, HAS-BLED outperformed all other bleeding risk scores for major bleeding (all p<0.001). C-indexes for ATRIA and ORBIT scores suggested no significant prediction for ICH. All contemporary bleeding risk scores had modest predictive value for predicting major bleeding but the best predictive value and NRI was found for the HAS-BLED score. Simply depending on modifiable bleeding risk factors had suboptimal predictive value for the prediction of major bleeding in AF patients, when compared to the HAS-BLED score. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.
Strategies to predict rheumatoid arthritis development in at-risk populations
van der Helm-van Mil, Annette H.
2016-01-01
The development of RA is conceived as a multiple hit process and the more hits that are acquired, the greater the risk of developing clinically apparent RA. Several at-risk phases have been described, including the presence of genetic and environmental factors, RA-related autoantibodies and biomarkers and symptoms. Intervention in these preclinical phases may be more effective compared with intervention in the clinical phase. One prerequisite for preventive strategies is the ability to estimate an individual’s risk adequately. This review evaluates the ability to predict the risk of RA in the various preclinical stages. Present data suggest that a combination of genetic and environmental factors is helpful to identify persons at high risk of RA among first-degree relatives. Furthermore, a combination of symptoms, antibody characteristics and environmental factors has been shown to be relevant for risk prediction in seropositive arthralgia patients. Large prospective studies are needed to validate and improve risk prediction in preclinical disease stages. PMID:25096602
Dumont, F; Tilly, C; Dartigues, P; Goéré, D; Honoré, C; Elias, D
2015-09-01
Low rectal cancers carry a high risk of circumferential margin involvement (CRM+). The anatomy of the lower part of the rectum and a long course of chemoradiotherapy (CRT) limit the accuracy of imaging to predict the CRM+. Additional criteria are required. Eighty six patients undergoing rectal resection with a sphincter-sparing procedure after CRT for low rectal cancer between 2000 and 2013 were retrospectively reviewed. Risk factors of CRM+ and the cut-off number of risk factors required to accurately predict the CRM+ were analyzed. The CRM+ rate was 9.3% and in the multivariate analysis, the significant risk factors were a tumor size exceeding 3 cm, poor response to CRT and a fixed tumor. The best cut-off to predict CRM+ was the presence of 2 risk factors. Patients with 0-1 and 2-3 risk factors had a CRM+ respectively in 1.3% and 50% of cases and a 3-year recurrence rate of 7% and 35% after a median follow-up of 50 months. Poor response, a residual tumor greater than 3 cm and a fixed tumor are predictive of CRM+. Sphincter sparing is an oncological safety procedure for patients with 0-1 criteria but not for patients with 2-3 criteria. Copyright © 2015 Elsevier Ltd. All rights reserved.
Hendry, Melissa C; Douglas, Kevin S; Winter, Elizabeth A; Edens, John F
2013-01-01
Much of the risk assessment literature has focused on the predictive validity of risk assessment tools. However, these tools often comprise a list of risk factors that are themselves complex constructs, and focusing on the quality of measurement of individual risk factors may improve the predictive validity of the tools. The present study illustrates this concern using the Antisocial Features and Aggression scales of the Personality Assessment Inventory (Morey, 1991). In a sample of 1,545 prison inmates and offenders undergoing treatment for substance abuse (85% male), we evaluated (a) the factorial validity of the ANT and AGG scales, (b) the utility of original ANT and AGG scales and newly derived ANT and AGG scales for predicting antisocial outcomes (recidivism and institutional infractions), and (c) whether items with a stronger relationship to the underlying constructs (higher factor loadings) were in turn more strongly related to antisocial outcomes. Confirmatory factor analyses (CFAs) indicated that ANT and AGG items were not structured optimally in these data in terms of correspondence to the subscale structure identified in the PAI manual. Exploratory factor analyses were conducted on a random split-half of the sample to derive optimized alternative factor structures, and cross-validated in the second split-half using CFA. Four-factor models emerged for both the ANT and AGG scales, and, as predicted, the size of item factor loadings was associated with the strength with which items were associated with institutional infractions and community recidivism. This suggests that the quality by which a construct is measured is associated with its predictive strength. Implications for risk assessment are discussed. Copyright © 2013 John Wiley & Sons, Ltd.
The mathematical limits of genetic prediction for complex chronic disease.
Keyes, Katherine M; Smith, George Davey; Koenen, Karestan C; Galea, Sandro
2015-06-01
Attempts at predicting individual risk of disease based on common germline genetic variation have largely been disappointing. The present paper formalises why genetic prediction at the individual level is and will continue to have limited utility given the aetiological architecture of most common complex diseases. Data were simulated on one million populations with 10 000 individuals in each populations with varying prevalences of a genetic risk factor, an interacting environmental factor and the background rate of disease. The determinant risk ratio and risk difference magnitude for the association between a gene variant and disease is a function of the prevalence of the interacting factors that activate the gene, and the background rate of disease. The risk ratio and total excess cases due to the genetic factor increase as the prevalence of interacting factors increase, and decrease as the background rate of disease increases. Germline genetic variations have high predictive capacity for individual disease only under conditions of high heritability of particular genetic sequences, plausible only under rare variant hypotheses. Under a model of common germline genetic variants that interact with other genes and/or environmental factors in order to cause disease, the predictive capacity of common genetic variants is determined by the prevalence of the factors that interact with the variant and the background rate. A focus on estimating genetic associations for the purpose of prediction without explicitly grounding such work in an understanding of modifiable (including environmentally influenced) factors will be limited in its ability to yield important insights about the risk of disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Kwok, Timothy Chi Yui; Su, Yi; Khoo, Chyi Chyi; Leung, Jason; Kwok, Anthony; Orwoll, Eric; Woo, Jean; Leung, Ping Chung
2017-05-01
Clinical risk factors to predict fracture are useful in guiding management of patients with osteoporosis or falls. Clinical predictors may however be population specific because of differences in lifestyle, environment and ethnicity. Four thousand community-dwelling Chinese males and females with average ages of 72.4 and 72.6 years were followed up for incident fractures, with an average of 6.5 and 8.8 years, respectively. Clinical information was collected, and bone mineral density (BMD) measurements were carried out at baseline. Stepwise Cox regression models were used to identify risk factors of nonvertebral fractures, with BMD as covariate. Areas under the receiver-operating characteristic (ROC) curve (AUC) were compared among different risk models. The incidence rates of nonvertebral fractures were 10.3 and 20.5 per 1000 person years in males and females, respectively. In males, age ≥80, history of a fall in the past year, fracture history, chronic obstructive pulmonary disease, impaired visual depth perception and low physical health-related quality of life were significant fracture risk factors, independent of BMD. In females, the significant factors were fracture history, low visual acuity and slow narrow walking speed. The clinical risk factors had a significant influence on fracture risk irrespective of osteoporosis status, even having a better risk discrimination than BMD alone, especially in males. The best risk prediction model consisted both BMD and clinical risk factors. Clinical risk factors have additive value to hip BMD in predicting nonvertebral fractures in older Chinese people and may predict them better than BMD alone in older Chinese males.
Vance, J Eric; Bowen, Natasha K; Fernandez, Gustavo; Thompson, Shealy
2002-01-01
To identify predictors of behavioral outcomes in high-risk adolescents with aggression and serious emotional disturbance (SED). Three hundred thirty-seven adolescents from a statewide North Carolina treatment program for aggressive youths with SED were followed between July 1995 and June 1999 from program entry (T1) to approximately 1 year later (T2). Historical and current psychosocial risk and protective factors as well as psychiatric symptom severity at T1 were tested as predictors of high and low behavioral functioning at T2. Behavioral functioning was a composite based on the frequency of risk-taking, self-injurious, threatening, and assaultive behavior. Eleven risk and protective factors were predictive of T2 behavioral functioning, while none of the measured T1 psychiatric symptoms was predictive. A history of aggression and negative parent-child relationships in childhood was predictive of worse T2 behavior, as was lower IQ. Better T2 behavioral outcomes were predicted by a history of consistent parental employment and positive parent-child relations, higher levels of current family support, contact with prosocial peers, higher reading level, good problem-solving abilities, and superior interpersonal skills. Among high-risk adolescents with aggression and SED, psychiatric symptom severity may be a less important predictor of behavioral outcomes than certain risk and protective factors. Several factors predictive of good behavioral functioning represent feasible intervention targets.
A Bayesian network model for predicting type 2 diabetes risk based on electronic health records
NASA Astrophysics Data System (ADS)
Xie, Jiang; Liu, Yan; Zeng, Xu; Zhang, Wu; Mei, Zhen
2017-07-01
An extensive, in-depth study of diabetes risk factors (DBRF) is of crucial importance to prevent (or reduce) the chance of suffering from type 2 diabetes (T2D). Accumulation of electronic health records (EHRs) makes it possible to build nonlinear relationships between risk factors and diabetes. However, the current DBRF researches mainly focus on qualitative analyses, and the inconformity of physical examination items makes the risk factors likely to be lost, which drives us to study the novel machine learning approach for risk model development. In this paper, we use Bayesian networks (BNs) to analyze the relationship between physical examination information and T2D, and to quantify the link between risk factors and T2D. Furthermore, with the quantitative analyses of DBRF, we adopt EHR and propose a machine learning approach based on BNs to predict the risk of T2D. The experiments demonstrate that our approach can lead to better predictive performance than the classical risk model.
Payne, Rupert A
2012-01-01
Cardiovascular disease is a major, growing, worldwide problem. It is important that individuals at risk of developing cardiovascular disease can be effectively identified and appropriately stratified according to risk. This review examines what we understand by the term risk, traditional and novel risk factors, clinical scoring systems, and the use of risk for informing prescribing decisions. Many different cardiovascular risk factors have been identified. Established, traditional factors such as ageing are powerful predictors of adverse outcome, and in the case of hypertension and dyslipidaemia are the major targets for therapeutic intervention. Numerous novel biomarkers have also been described, such as inflammatory and genetic markers. These have yet to be shown to be of value in improving risk prediction, but may represent potential therapeutic targets and facilitate more targeted use of existing therapies. Risk factors have been incorporated into several cardiovascular disease prediction algorithms, such as the Framingham equation, SCORE and QRISK. These have relatively poor predictive power, and uncertainties remain with regards to aspects such as choice of equation, different risk thresholds and the roles of relative risk, lifetime risk and reversible factors in identifying and treating at-risk individuals. Nonetheless, such scores provide objective and transparent means of quantifying risk and their integration into therapeutic guidelines enables equitable and cost-effective distribution of health service resources and improves the consistency and quality of clinical decision making. PMID:22348281
Advantages of new cardiovascular risk-assessment strategies in high-risk patients with hypertension.
Ruilope, Luis M; Segura, Julian
2005-10-01
Accurate assessment of cardiovascular disease (CVD) risk in patients with hypertension is important when planning appropriate treatment of modifiable risk factors. The causes of CVD are multifactorial, and hypertension seldom exists as an isolated risk factor. Classic models of risk assessment are more accurate than a simple counting of risk factors, but they are not generalizable to all populations. In addition, the risk associated with hypertension is graded, continuous, and independent of other risk factors, and this is not reflected in classic models of risk assessment. This article is intended to review both classic and newer models of CVD risk assessment. MEDLINE was searched for articles published between 1990 and 2005 that contained the terms cardiovascular disease, hypertension, or risk assessment. Articles describing major clinical trials, new data about cardiovascular risk, or global risk stratification were selected for review. Some patients at high long-term risk for CVD events (eg, patients aged <50 years with multiple risk factors) may go untreated because they do not meet the absolute risk-intervention threshold of 20% risk over 10 years with the classic model. Recognition of the limitations of classic risk-assessment models led to new guidelines, particularly those of the European Society of Hypertension-European Society of Cardiology. These guidelines view hypertension as one of many risk and disease factors that require treatment to decrease risk. These newer guidelines include a more comprehensive range of risk factors and more finely graded blood pressure ranges to stratify patients by degree of risk. Whether they accurately predict CVD risk in most populations is not known. Evidence from the Valsartan Antihypertensive Long-term Use Evaluation (VALUE) study, which stratified patients by several risk and disease factors, highlights the predictive value of some newer CVD risk assessments. Modern risk assessments, which include blood pressure along with a wide array of modifiable risk factors, may be more accurate than classic models for CVD risk prediction.
Behavioral Risk Assessment From Newborn to Preschool: The Value of Older Siblings.
Rodrigues, Michelle; Binnoon-Erez, Noam; Plamondon, Andre; Jenkins, Jennifer M
2017-08-01
The aim of this study was to examine the plausibility of a risk prediction tool in infancy for school-entry emotional and behavioral problems. Familial aggregation has been operationalized previously as maternal psychopathology. The hypothesis was tested that older sibling (OS) psychopathology, as an indicator of familial aggregation, would enable a fair level of risk prediction compared with previous research, when combined with traditional risk factors. By using a longitudinal design, data on child and family risk factors were collected on 323 infants ( M = 2.00 months), all of whom had OSs. Infants were followed up 4.5 years later when both parents provided ratings of emotional and behavioral problems. Multiple regression and receiver operating characteristic curve analyses were conducted for emotional, conduct, and attention problems separately. The emotional and behavioral problems of OSs at infancy were the strongest predictors of the same problems in target children 4.5 years later. Other risk factors, including maternal depression and socioeconomic status provided extra, but weak, significant prediction. The area under the receiver operating characteristic curve for emotional and conduct problems yielded a fair prediction. This study is the first to offer a fair degree of prediction from risk factors at birth to school-entry emotional and behavioral problems. This degree of prediction was achieved with the inclusion of the emotional and behavioral problems of OSs (thus limiting generalizability to children with OSs). The inclusion of OS psychopathology raises risk prediction to a fair level. Copyright © 2017 by the American Academy of Pediatrics.
Utilizing Dental Electronic Health Records Data to Predict Risk for Periodontal Disease.
Thyvalikakath, Thankam P; Padman, Rema; Vyawahare, Karnali; Darade, Pratiksha; Paranjape, Rhucha
2015-01-01
Periodontal disease is a major cause for tooth loss and adversely affects individuals' oral health and quality of life. Research shows its potential association with systemic diseases like diabetes and cardiovascular disease, and social habits such as smoking. This study explores mining potential risk factors from dental electronic health records to predict and display patients' contextualized risk for periodontal disease. We retrieved relevant risk factors from structured and unstructured data on 2,370 patients who underwent comprehensive oral examinations at the Indiana University School of Dentistry, Indianapolis, IN, USA. Predicting overall risk and displaying relationships between risk factors and their influence on the patient's oral and general health can be a powerful educational and disease management tool for patients and clinicians at the point of care.
Nicoll, R; Wiklund, U; Zhao, Y; Diederichsen, A; Mickley, H; Ovrehus, K; Zamorano, J; Gueret, P; Schmermund, A; Maffei, E; Cademartiri, F; Budoff, M; Henein, M
2016-09-01
The influence of gender and age on risk factor prediction of coronary artery calcification (CAC) in symptomatic patients is unclear. From the European Calcific Coronary Artery Disease (EURO-CCAD) cohort, we retrospectively investigated 6309 symptomatic patients, 62% male, from Denmark, France, Germany, Italy, Spain and USA. All of them underwent risk factor assessment and CT scanning for CAC scoring. The prevalence of CAC among females was lower than among males in all age groups. Using multivariate logistic regression, age, dyslipidaemia, hypertension, diabetes and smoking were independently predictive of CAC presence in both genders. In addition to a progressive increase in CAC with age, the most important predictors of CAC presence were dyslipidaemia and diabetes (β = 0.64 and 0.63, respectively) in males and diabetes (β = 1.08) followed by smoking (β = 0.68) in females; these same risk factors were also important in predicting increasing CAC scores. There was no difference in the predictive ability of diabetes, hypertension and dyslipidaemia in either gender for CAC presence in patients aged <50 and 50-70 years. However, in patients aged >70, only dyslipidaemia predicted CAC presence in males and only smoking and diabetes were predictive in females. In symptomatic patients, there are significant differences in the ability of conventional risk factors to predict CAC presence between genders and between patients aged <70 and ≥70, indicating the important role of age in predicting CAC presence. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Testing the Predictive Validity of the Hendrich II Fall Risk Model.
Jung, Hyesil; Park, Hyeoun-Ae
2018-03-01
Cumulative data on patient fall risk have been compiled in electronic medical records systems, and it is possible to test the validity of fall-risk assessment tools using these data between the times of admission and occurrence of a fall. The Hendrich II Fall Risk Model scores assessed during three time points of hospital stays were extracted and used for testing the predictive validity: (a) upon admission, (b) when the maximum fall-risk score from admission to falling or discharge, and (c) immediately before falling or discharge. Predictive validity was examined using seven predictive indicators. In addition, logistic regression analysis was used to identify factors that significantly affect the occurrence of a fall. Among the different time points, the maximum fall-risk score assessed between admission and falling or discharge showed the best predictive performance. Confusion or disorientation and having a poor ability to rise from a sitting position were significant risk factors for a fall.
Rajadhyaksha, Manoj; Subramanyam, Meena; Rup, Bonnie
2013-10-01
The immunogenicity profile of a biotherapeutic is determined by multiple product-, process- or manufacturing-, patient- and treatment-related factors and the bioanalytical methodology used to monitor for immunogenicity. This creates a complex situation that limits direct correlation of individual factors to observed immunogenicity rates. Therefore, mechanistic understanding of how these factors individually or in concert could influence the overall incidence and clinical risk of immunogenicity is crucial to provide the best benefit/risk profile for a given biotherapeutic in a given indication and to inform risk mitigation strategies. Advances in the field of immunogenicity have included development of best practices for monitoring anti-drug antibody development, categorization of risk factors contributing to immunogenicity, development of predictive tools, and development of effective strategies for risk management and mitigation. Thus, the opportunity to ask "where we are now and where we would like to go from here?" was the main driver for organizing an Open Forum on Improving Immunogenicity Risk Prediction and Management, conducted at the 2012 American Association of Pharmaceutical Scientists' (AAPS) National Biotechnology Conference in San Diego. The main objectives of the Forum include the following: to understand the nature of immunogenicity risk factors, to identify analytical tools used and animal models and management strategies needed to improve their predictive value, and finally to identify collaboration opportunities to improve the reliability of risk prediction, mitigation, and management. This meeting report provides the Forum participant's and author's perspectives on the barriers to advancing this field and recommendations for overcoming these barriers through collaborative efforts.
Namazi Shabestari, Alireza; Asadi, Mojgan; Jouyandeh, Zahra; Qorbani, Mostafa; Kelishadi, Roya
2016-06-01
The lipid accumulation product is a novel, safe and inexpensive index of central lipid over accumulation based on waist circumference and fasting concentration of circulating triglycerides. This study was designed to investigate the ability of lipid accumulation product to predict Cardio-metabolic risk factors in postmenopausal women. In this Cross-sectional study, 264 postmenopausal women by using convenience sampling method were selected from menopause clinic in Tehran. Cardio-metabolic risk factors were measured, and lipid accumulation product (waist-58×triglycerides [nmol/L]) was calculated. Optimal cut-off point of lipid accumulation product for predicting metabolic syndrome was estimated by ROC (Receiver-operating characteristic) curve analysis. Metabolic syndrome was diagnosed in 41.2% of subjects. Optimal cut-off point of lipid accumulation product for predicting metabolic syndrome was 47.63 (sensitivity:75%; specificity:77.9%). High lipid accumulation product increases risk of all Cardio-metabolic risk factors except overweight, high Total Cholesterol, high Low Density Lipoprotein Cholesterol and high Fasting Blood Sugar in postmenopausal women. Our findings show that lipid accumulation product is associated with metabolic syndrome and some Cardio-metabolic risk factors Also lipid accumulation product may have been a useful tool for predicting cardiovascular disease and metabolic syndrome risk in postmenopausal women.
Seyednasrollah, Fatemeh; Mäkelä, Johanna; Pitkänen, Niina; Juonala, Markus; Hutri-Kähönen, Nina; Lehtimäki, Terho; Viikari, Jorma; Kelly, Tanika; Li, Changwei; Bazzano, Lydia; Elo, Laura L; Raitakari, Olli T
2017-06-01
Obesity is a known risk factor for cardiovascular disease. Early prediction of obesity is essential for prevention. The aim of this study is to assess the use of childhood clinical factors and the genetic risk factors in predicting adulthood obesity using machine learning methods. A total of 2262 participants from the Cardiovascular Risk in YFS (Young Finns Study) were followed up from childhood (age 3-18 years) to adulthood for 31 years. The data were divided into training (n=1625) and validation (n=637) set. The effect of known genetic risk factors (97 single-nucleotide polymorphisms) was investigated as a weighted genetic risk score of all 97 single-nucleotide polymorphisms (WGRS97) or a subset of 19 most significant single-nucleotide polymorphisms (WGRS19) using boosting machine learning technique. WGRS97 and WGRS19 were validated using external data (n=369) from BHS (Bogalusa Heart Study). WGRS19 improved the accuracy of predicting adulthood obesity in training (area under the curve [AUC=0.787 versus AUC=0.744, P <0.0001) and validation data (AUC=0.769 versus AUC=0.747, P =0.026). WGRS97 improved the accuracy in training (AUC=0.782 versus AUC=0.744, P <0.0001) but not in validation data (AUC=0.749 versus AUC=0.747, P =0.785). Higher WGRS19 associated with higher body mass index at 9 years and WGRS97 at 6 years. Replication in BHS confirmed our findings that WGRS19 and WGRS97 are associated with body mass index. WGRS19 improves prediction of adulthood obesity. Predictive accuracy is highest among young children (3-6 years), whereas among older children (9-18 years) the risk can be identified using childhood clinical factors. The model is helpful in screening children with high risk of developing obesity. © 2017 American Heart Association, Inc.
Risk factors for early adolescent drug use in four ethnic and racial groups.
Vega, W A; Zimmerman, R S; Warheit, G J; Apospori, E; Gil, A G
1993-02-01
It is widely believed that risk factors identified in previous epidemiologic studies accurately predict adolescent drug use. Comparative studies are needed to determine how risk factors vary in prevalence, distribution, sensitivity, and pattern across the major US ethnic/racial groups. Baseline questionnaire data from a 3-year epidemiologic study of early adolescent development and drug use were used to conduct bivariate and multivariate risk factor analyses. Respondents (n = 6760) were sixth- and seventh-grade Cuban, other Hispanic, Black, and White non-Hispanic boys in the 48 middle schools of the greater Miami (Dade County) area. Findings indicate 5% lifetime illicit drug use, 4% lifetime inhalant use, 37% lifetime alcohol use, and 21% lifetime tobacco use, with important intergroup differences. Monotonic relationships were found between 10 risk factors and alcohol and illicit drug use. Individual risk factors were distributed disproportionately, and sensitivity and patterning of risk factors varied widely by ethnic/racial subsample. While the cumulative prevalence of risk factors bears a monotonic relationship to drug use, ethnic/racial differences in risk factor profiles, especially for Blacks, suggest differential predictive value based on cultural differences.
Pecoraro, Felice; Gloekler, Steffen; Mader, Caecilia E; Roos, Malgorzata; Chaykovska, Lyubov; Veith, Frank J; Cayne, Neal S; Mangialardi, Nicola; Neff, Thomas; Lachat, Mario
2018-03-01
The background of this paper is to report the mortality at 30 and 90 days and at mean follow-up after open abdominal aortic aneurysms (AAA) emergent repair and to identify predictive risk factors for 30- and 90-day mortality. Between 1997 and 2002, 104 patients underwent emergent AAA open surgery. Symptomatic and ruptured AAAs were observed, respectively, in 21 and 79% of cases. Mean patient age was 70 (SD 9.2) years. Mean aneurysm maximal diameter was 7.4 (SD 1.6) cm. Primary endpoints were 30- and 90-day mortality. Significant mortality-related risk factor identification was the secondary endpoint. Open repair trend and its related perioperative mortality with a per-year analysis and a correlation subanalysis to identify predictive mortality factor were performed. Mean follow-up time was 23 (SD 23) months. Overall, 30-day mortality was 30%. Significant mortality-related risk factors were the use of computed tomography (CT) as a preoperative diagnostic tool, AAA rupture, preoperative shock, intraoperative cardiopulmonary resuscitation (CPR), use of aortic balloon occlusion, intraoperative massive blood transfusion (MBT), and development of abdominal compartment syndrome (ACS). Previous abdominal surgery was identified as a protective risk factor. The mortality rate at 90 days was 44%. Significant mortality-related risk factors were AAA rupture, aortocaval fistula, peripheral artery disease (PAD), preoperative shock, CPR, MBT, and ACS. The mortality rate at follow-up was 45%. Correlation analysis showed that MBT, shock, and ACS are the most relevant predictive mortality factor at 30 and 90 days. During the transition period from open to endovascular repair, open repair mortality outcomes remained comparable with other contemporary data despite a selection bias for higher risk patients. MBT, shock, and ACS are the most pronounced predictive mortality risk factors.
Wen, Lei
2017-08-20
Aspirin is widely used for the prevention of cardiovascular and cerebrovascular diseases for the past few years. However, much attention has been paid to the adverse effects associated with aspirin such as gastrointestinal bleeding. How to weigh the benefits and hazards? The current study aimed to assess the feasibility of a cardiovascular/gastrointestinal risk calculator, AsaRiskCalculator, in predicting gastrointestinal events in Chinese patients with myocardial infarction (MI), determining unique risk factor(s) for gastrointestinal events to be considered in the calculator. The MI patients who visited Shapingba District People's Hospital between January 2012 and January 2016 were retrospectively reviewed. Based on gastroscopic data, the patients were divided into two groups: gastrointestinal and nongastrointestinal groups. Demographic and clinical data of the patients were then retrieved for statistical analysis. Univariate and multiple logistic regression analyses were used to identify independent risk factors for gastrointestinal events. The receiver operating characteristic (ROC) curves were used to assess the predictive value of AsaRiskCalculator for gastrointestinal events. A total of 400 MI patients meeting the eligibility criteria were analyzed, including 94 and 306 in the gastrointestinal and nongastrointestinal groups, respectively. The data showed that age, male gender, predicted gastrointestinal events, and Helicobacter pylori (HP) infection were positively correlated with gastrointestinal events. In multiple logistic regression analysis, predicted gastrointestinal events and HP infection were identified as risk factors for actual gastrointestinal events. HP infection was highly predictive in Chinese patients; the ROC curve indicated an area under the curve of 0.822 (95% confidence interval: 0.774-0.870). The best diagnostic cutoff point of predicted gastrointestinal events was 68.0‰, yielding sensitivity and specificity of 60.6% and 93.1%, respectively, for predicting gastrointestinal events in Chinese patients with MI. AsaRiskCalculator had a predictive value for gastrointestinal events in Chinese patients with MI. HP infection seemed to be an independent risk factor for gastrointestinal events caused by long-term aspirin treatment in Chinese patients with MI, and it should be included in the risk calculator adapted for Chinese patients.
Arthur, Michael W; Brown, Eric C; Briney, John S; Hawkins, J David; Abbott, Robert D; Catalano, Richard F; Becker, Linda; Langer, Michael; Mueller, Martin T
2015-08-01
School administrators and teachers face difficult decisions about how best to use school resources to meet academic achievement goals. Many are hesitant to adopt prevention curricula that are not focused directly on academic achievement. Yet, some have hypothesized that prevention curricula can remove barriers to learning and, thus, promote achievement. We examined relationships among school levels of student substance use and risk and protective factors that predict adolescent problem behaviors and achievement test performance. Hierarchical generalized linear models were used to predict associations involving school-averaged levels of substance use and risk and protective factors and students' likelihood of meeting achievement test standards on the Washington Assessment of Student Learning, statistically controlling for demographic and economic factors known to be associated with achievement. Levels of substance use and risk/protective factors predicted the academic test score performance of students. Many of these effects remained significant even after controlling for model covariates. Implementing prevention programs that target empirically identified risk and protective factors has the potential to have a favorable effect on students' academic achievement. © 2015, American School Health Association.
Beck, J D; Weintraub, J A; Disney, J A; Graves, R C; Stamm, J W; Kaste, L M; Bohannan, H M
1992-12-01
The purpose of this analysis is to compare three different statistical models for predicting children likely to be at risk of developing dental caries over a 3-yr period. Data are based on 4117 children who participated in the University of North Carolina Caries Risk Assessment Study, a longitudinal study conducted in the Aiken, South Carolina, and Portland, Maine areas. The three models differed with respect to either the types of variables included or the definition of disease outcome. The two "Prediction" models included both risk factor variables thought to cause dental caries and indicator variables that are associated with dental caries, but are not thought to be causal for the disease. The "Etiologic" model included only etiologic factors as variables. A dichotomous outcome measure--none or any 3-yr increment, was used in the "Any Risk Etiologic model" and the "Any Risk Prediction Model". Another outcome, based on a gradient measure of disease, was used in the "High Risk Prediction Model". The variables that are significant in these models vary across grades and sites, but are more consistent among the Etiologic model than the Predictor models. However, among the three sets of models, the Any Risk Prediction Models have the highest sensitivity and positive predictive values, whereas the High Risk Prediction Models have the highest specificity and negative predictive values. Considerations in determining model preference are discussed.
Kingston, Drew A; Fedoroff, Paul; Firestone, Philip; Curry, Susan; Bradford, John M
2008-01-01
In this study, we examined the unique contribution of pornography consumption to the longitudinal prediction of criminal recidivism in a sample of 341 child molesters. We specifically tested the hypothesis, based on predictions informed by the confluence model of sexual aggression that pornography will be a risk factor for recidivism only for those individuals classified as relatively high risk for re-offending. Pornography use (frequency and type) was assessed through self-report and recidivism was measured using data from a national database from the Royal Canadian Mounted Police. Indices of recidivism, which were assessed up to 15 years after release, included an overall criminal recidivism index, as well as subcategories focusing on violent (including sexual) recidivism and sexual recidivism alone. Results for both frequency and type of pornography use were generally consistent with our predictions. Most importantly, after controlling for general and specific risk factors for sexual aggression, pornography added significantly to the prediction of recidivism. Statistical interactions indicated that frequency of pornography use was primarily a risk factor for higher-risk offenders, when compared with lower-risk offenders, and that content of pornography (i.e., pornography containing deviant content) was a risk factor for all groups. The importance of conceptualizing particular risk factors (e.g., pornography), within the context of other individual characteristics is discussed.
Predicting adolescent's cyberbullying behavior: A longitudinal risk analysis.
Barlett, Christopher P
2015-06-01
The current study used the risk factor approach to test the unique and combined influence of several possible risk factors for cyberbullying attitudes and behavior using a four-wave longitudinal design with an adolescent US sample. Participants (N = 96; average age = 15.50 years) completed measures of cyberbullying attitudes, perceptions of anonymity, cyberbullying behavior, and demographics four times throughout the academic school year. Several logistic regression equations were used to test the contribution of these possible risk factors. Results showed that (a) cyberbullying attitudes and previous cyberbullying behavior were important unique risk factors for later cyberbullying behavior, (b) anonymity and previous cyberbullying behavior were valid risk factors for later cyberbullying attitudes, and (c) the likelihood of engaging in later cyberbullying behavior increased with the addition of risk factors. Overall, results show the unique and combined influence of such risk factors for predicting later cyberbullying behavior. Results are discussed in terms of theory. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
Predicting Time to Hospital Discharge for Extremely Preterm Infants
Hintz, Susan R.; Bann, Carla M.; Ambalavanan, Namasivayam; Cotten, C. Michael; Das, Abhik; Higgins, Rosemary D.
2010-01-01
As extremely preterm infant mortality rates have decreased, concerns regarding resource utilization have intensified. Accurate models to predict time to hospital discharge could aid in resource planning, family counseling, and perhaps stimulate quality improvement initiatives. Objectives For infants <27 weeks estimated gestational age (EGA), to develop, validate and compare several models to predict time to hospital discharge based on time-dependent covariates, and based on the presence of 5 key risk factors as predictors. Patients and Methods This was a retrospective analysis of infants <27 weeks EGA, born 7/2002-12/2005 and surviving to discharge from a NICHD Neonatal Research Network site. Time to discharge was modeled as continuous (postmenstrual age at discharge, PMAD), and categorical variables (“Early” and “Late” discharge). Three linear and logistic regression models with time-dependent covariate inclusion were developed (perinatal factors only, perinatal+early neonatal factors, perinatal+early+later factors). Models for Early and Late discharge using the cumulative presence of 5 key risk factors as predictors were also evaluated. Predictive capabilities were compared using coefficient of determination (R2) for linear models, and AUC of ROC curve for logistic models. Results Data from 2254 infants were included. Prediction of PMAD was poor, with only 38% of variation explained by linear models. However, models incorporating later clinical characteristics were more accurate in predicting “Early” or “Late” discharge (full models: AUC 0.76-0.83 vs. perinatal factor models: AUC 0.56-0.69). In simplified key risk factors models, predicted probabilities for Early and Late discharge compared favorably with observed rates. Furthermore, the AUC (0.75-0.77) were similar to those of models including the full factor set. Conclusions Prediction of Early or Late discharge is poor if only perinatal factors are considered, but improves substantially with knowledge of later-occurring morbidities. Prediction using a few key risk factors is comparable to full models, and may offer a clinically applicable strategy. PMID:20008430
Configurations of Common Childhood Psychosocial Risk Factors
ERIC Educational Resources Information Center
Copeland, William; Shanahan, Lilly; Costello, E. Jane; Angold, Adrian
2009-01-01
Background: Co-occurrence of psychosocial risk factors is commonplace, but little is known about psychiatrically-predictive configurations of psychosocial risk factors. Methods: Latent class analysis (LCA) was applied to 17 putative psychosocial risk factors in a representative population sample of 920 children ages 9 to 17. The resultant class…
Assessing Bleeding Risk in Patients Taking Anticoagulants
Shoeb, Marwa; Fang, Margaret C.
2013-01-01
Anticoagulant medications are commonly used for the prevention and treatment of thromboembolism. Although highly effective, they are also associated with significant bleeding risks. Numerous individual clinical factors have been linked to an increased risk of hemorrhage, including older age, anemia, and renal disease. To help quantify hemorrhage risk for individual patients, a number of clinical risk prediction tools have been developed. These risk prediction tools differ in how they were derived and how they identify and weight individual risk factors. At present, their ability to effective predict anticoagulant-associated hemorrhage remains modest. Use of risk prediction tools to estimate bleeding in clinical practice is most influential when applied to patients at the lower spectrum of thromboembolic risk, when the risk of hemorrhage will more strongly affect clinical decisions about anticoagulation. Using risk tools may also help counsel and inform patients about their potential risk for hemorrhage while on anticoagulants, and can identify patients who might benefit from more careful management of anticoagulation. PMID:23479259
Lee, Jeannette Y; Klimberg, Suzanne; Bondurant, Kristina L; Phillips, Martha M; Kadlubar, Susan A
2014-01-01
The Gail and CARE models estimate breast cancer risk for white and African-American (AA) women, respectively. The aims of this study were to compare metropolitan and nonmetropolitan women with respect to predicted breast cancer risks based on known risk factors, and to determine if population density was an independent risk factor for breast cancer risk. A cross-sectional survey was completed by 15,582 women between 35 and 85 years of age with no history of breast cancer. Metropolitan and nonmetropolitan women were compared with respect to risk factors, and breast cancer risk estimates, using general linear models adjusted for age. For both white and AA women, tisk factors used to estimate breast cancer risk included age at menarche, history of breast biopsies, and family history. For white women, age at first childbirth was an additional risk factor. In comparison to their nonmetropolitan counterparts, metropolitan white women were more likely to report having a breast biopsy, have family history of breast cancer, and delay childbirth. Among white metropolitan and nonmetropolitan women, mean estimated 5-year risks were 1.44% and 1.32% (p < 0.001), and lifetime risks of breast cancer were 10.81% and 10.01% (p < 0.001), respectively. AA metropolitan residents were more likely than those from nonmetropolitan areas to have had a breast biopsy. Among AA metropolitan and nonmetropolitan women, mean estimated 5-year risks were 1.16% and 1.12% (p = 0.039) and lifetime risks were 8.94%, and 8.85% (p = 0.344). Metropolitan residence was associated with higher predicted breast cancer risks for white women. Among AA women, metropolitan residence was associated with a higher predicted breast cancer risk at 5 years, but not over a lifetime. Population density was not an independent risk factor for breast cancer. © 2014 Wiley Periodicals, Inc.
Huang, Zhengxing; Dong, Wei; Duan, Huilong; Liu, Jiquan
2018-05-01
Acute coronary syndrome (ACS), as a common and severe cardiovascular disease, is a leading cause of death and the principal cause of serious long-term disability globally. Clinical risk prediction of ACS is important for early intervention and treatment. Existing ACS risk scoring models are based mainly on a small set of hand-picked risk factors and often dichotomize predictive variables to simplify the score calculation. This study develops a regularized stacked denoising autoencoder (SDAE) model to stratify clinical risks of ACS patients from a large volume of electronic health records (EHR). To capture characteristics of patients at similar risk levels, and preserve the discriminating information across different risk levels, two constraints are added on SDAE to make the reconstructed feature representations contain more risk information of patients, which contribute to a better clinical risk prediction result. We validate our approach on a real clinical dataset consisting of 3464 ACS patient samples. The performance of our approach for predicting ACS risk remains robust and reaches 0.868 and 0.73 in terms of both AUC and accuracy, respectively. The obtained results show that the proposed approach achieves a competitive performance compared to state-of-the-art models in dealing with the clinical risk prediction problem. In addition, our approach can extract informative risk factors of ACS via a reconstructive learning strategy. Some of these extracted risk factors are not only consistent with existing medical domain knowledge, but also contain suggestive hypotheses that could be validated by further investigations in the medical domain.
Posthumus, A G; Birnie, E; van Veen, M J; Steegers, E A P; Bonsel, G J
2016-07-01
in the Netherlands the perinatal mortality rate is high compared to other European countries. Around eighty percent of perinatal mortality cases is preceded by being small for gestational age (SGA), preterm birth and/or having a low Apgar-score at 5 minutes after birth. Current risk detection in pregnancy focusses primarily on medical risks. However, non-medical risk factors may be relevant too. Both non-medical and medical risk factors are incorporated in the Rotterdam Reproductive Risk Reduction (R4U) scorecard. We investigated the associations between R4U risk factors and preterm birth, SGA and a low Apgar score. a prospective cohort study under routine practice conditions. six midwifery practices and two hospitals in Rotterdam, the Netherlands. 836 pregnant women. the R4U scorecard was filled out at the booking visit. after birth, the follow-up data on pregnancy outcomes were collected. Multivariate logistic regression was used to fit models for the prediction of any adverse outcome (preterm birth, SGA and/or a low Apgar score), stratified for ethnicity and socio-economic status (SES). factors predicting any adverse outcome for Western women were smoking during the first trimester and over-the-counter medication. For non-Western women risk factors were teenage pregnancy, advanced maternal age and an obstetric history of SGA. Risk factors for high SES women were low family income, no daily intake of vegetables and a history of preterm birth. For low SES women risk factors appeared to be low family income, non-Western ethnicity, smoking during the first trimester and a history of SGA. the presence of both medical and non-medical risk factors early in pregnancy predict the occurrence of adverse outcomes at birth. Furthermore the risk profiles for adverse outcomes differed according to SES and ethnicity. to optimise effective risk selection, both medical and non-medical risk factors should be taken into account in midwifery and obstetric care at the booking visit. Copyright © 2016. Published by Elsevier Ltd.
NASA Technical Reports Server (NTRS)
Halm, M. K.; Clark, A.; Wear, M. L.; Murray, J. D.; Polk, J. D.; Amirian, E.
2009-01-01
Risk prediction equations from the Framingham Heart Study are commonly used to predict the absolute risk of myocardial infarction (MI) and coronary heart disease (CHD) related death. Predicting CHD-related events in the U.S. astronaut corps presents a monumental challenge, both because astronauts tend to live healthier lifestyles and because of the unique cardiovascular stressors associated with being trained for and participating in space flight. Traditional risk factors may not hold enough predictive power to provide a useful indicator of CHD risk in this unique population. It is important to be able to identify individuals who are at higher risk for CHD-related events so that appropriate preventive care can be provided. This is of special importance when planning long duration missions since the ability to provide advanced cardiac care and perform medical evacuation is limited. The medical regimen of the astronauts follows a strict set of clinical practice guidelines in an effort to ensure the best care. The purpose of this study was to evaluate the utility of the Framingham risk score (FRS), low-density lipoprotein (LDL) and high-density lipoprotein levels, blood pressure, and resting pulse as predictors of CHD-related death and MI in the astronaut corps, using Cox regression. Of these factors, only two, LDL and pulse at selection, were predictive of CHD events (HR(95% CI)=1.12 (1.00-1.25) and HR(95% CI)=1.70 (1.05-2.75) for every 5-unit increase in LDL and pulse, respectively). Since traditional CHD risk factors may lack the specificity to predict such outcomes in astronauts, the development of a new predictive model, using additional measures such as electron-beam computed tomography and carotid intima-media thickness ultrasound, is planned for the future.
Suicide risk assessment: Trust an implicit probe or listen to the patient?
Harrison, Dominique P; Stritzke, Werner G K; Fay, Nicolas; Hudaib, Abdul-Rahman
2018-05-21
Previous research suggests implicit cognition can predict suicidal behavior. This study examined the utility of the death/suicide implicit association test (d/s-IAT) in acute and prospective assessment of suicide risk and protective factors, relative to clinician and patient estimates of future suicide risk. Patients (N = 128; 79 female; 111 Caucasian) presenting to an emergency department were recruited if they reported current suicidal ideation or had been admitted because of an acute suicide attempt. Patients completed the d/s-IAT and self-report measures assessing three death-promoting (e.g., suicide ideation) and two life-sustaining (e.g., zest for life) factors, with self-report measures completed again at 3- and 6-month follow-ups. The clinician and patient provided risk estimates of that patient making a suicide attempt within the next 6 months. Results showed that among current attempters, the d/s-IAT differentiated between first time and multiple attempters; with multiple attempters having significantly weaker self-associations with life relative to death. The d/s-IAT was associated with concurrent suicidal ideation and zest for life, but only predicted the desire to die prospectively at 3 months. By contrast, clinician and patient estimates predicted suicide risk at 3- and 6-month follow-up, with clinician estimates predicting death-promoting factors, and only patient estimates predicting life-sustaining factors. The utility of the d/s-IAT was more pronounced in the assessment of concurrent risk. Prospectively, clinician and patient predictions complemented each other in predicting suicide risk and resilience, respectively. Our findings indicate collaborative rather than implicit approaches add greater value to the management of risk and recovery in suicidal patients. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Proposal for a recovery prediction method for patients affected by acute mediastinitis
2012-01-01
Background An attempt to find a prediction method of death risk in patients affected by acute mediastinitis. There is not such a tool described in available literature for that serious disease. Methods The study comprised 44 consecutive cases of acute mediastinitis. General anamnesis and biochemical data were included. Factor analysis was used to extract the risk characteristic for the patients. The most valuable results were obtained for 8 parameters which were selected for further statistical analysis (all collected during few hours after admission). Three factors reached Eigenvalue >1. Clinical explanations of these combined statistical factors are: Factor1 - proteinic status (serum total protein, albumin, and hemoglobin level), Factor2 - inflammatory status (white blood cells, CRP, procalcitonin), and Factor3 - general risk (age, number of coexisting diseases). Threshold values of prediction factors were estimated by means of statistical analysis (factor analysis, Statgraphics Centurion XVI). Results The final prediction result for the patients is constructed as simultaneous evaluation of all factor scores. High probability of death should be predicted if factor 1 value decreases with simultaneous increase of factors 2 and 3. The diagnostic power of the proposed method was revealed to be high [sensitivity =90%, specificity =64%], for Factor1 [SNC = 87%, SPC = 79%]; for Factor2 [SNC = 87%, SPC = 50%] and for Factor3 [SNC = 73%, SPC = 71%]. Conclusion The proposed prediction method seems a useful emergency signal during acute mediastinitis control in affected patients. PMID:22574625
Slade, Karen; Edelman, Robert
2014-01-01
Each year approximately 110,000 people are imprisoned in England and Wales and new prisoners remain one of the highest risk groups for suicide across the world. The reduction of suicide in prisoners remains difficult as assessments and interventions tend to rely on static risk factors with few theoretical or integrated models yet evaluated. To identify the dynamic factors that contribute to suicide ideation in this population based on Williams and Pollock's (2001) Cry of Pain (CoP) model. New arrivals (N = 198) into prison were asked to complete measures derived from the CoP model plus clinical and prison-specific factors. It was hypothesized that the factors of the CoP model would be predictive of suicide ideation. Support was provided for the defeat and entrapment aspects of the CoP model with previous self-harm, repeated times in prison, and suicide-permissive cognitions also key in predicting suicide ideation for prisoners on entry to prison. An integrated and dynamic model was developed that has utility in predicting suicide in early-stage prisoners. Implications for both theory and practice are discussed along with recommendations for future research.
Juhola, Jonna; Oikonen, Mervi; Magnussen, Costan G; Mikkilä, Vera; Siitonen, Niina; Jokinen, Eero; Laitinen, Tomi; Würtz, Peter; Gidding, Samuel S; Taittonen, Leena; Seppälä, Ilkka; Jula, Antti; Kähönen, Mika; Hutri-Kähönen, Nina; Lehtimäki, Terho; Viikari, Jorma S A; Juonala, Markus; Raitakari, Olli T
2012-07-24
Hypertension is a major modifiable cardiovascular risk factor. The present longitudinal study aimed to examine the best combination of childhood physical and environmental factors to predict adult hypertension and furthermore whether newly identified genetic variants for blood pressure increase the prediction of adult hypertension. The study cohort included 2625 individuals from the Cardiovascular Risk in Young Finns Study who were followed up for 21 to 27 years since baseline (1980; age, 3-18 years). In addition to dietary factors and biomarkers related to blood pressure, we examined whether a genetic risk score based on 29 newly identified single-nucleotide polymorphisms enhances the prediction of adult hypertension. Hypertension in adulthood was defined as systolic blood pressure ≥ 130 mm Hg and/or diastolic blood pressure ≥ 85 mm Hg or medication for the condition. Independent childhood risk factors for adult hypertension included the individual's own blood pressure (P<0.0001), parental hypertension (P<0.0001), childhood overweight/obesity (P=0.005), low parental occupational status (P=0.003), and high genetic risk score (P<0.0001). Risk assessment based on childhood overweight/obesity status, parental hypertension, and parental occupational status was superior in predicting hypertension compared with the approach using only data on childhood blood pressure levels (C statistics, 0.718 versus 0.733; P=0.0007). Inclusion of both parental hypertension history and data on novel genetic variants for hypertension further improved the C statistics (0.742; P=0.015). Prediction of adult hypertension was enhanced by taking into account known physical and environmental childhood risk factors, family history of hypertension, and novel genetic variants. A multifactorial approach may be useful in identifying children at high risk for adult hypertension.
Yu, Ya-Hui; Xia, Wei-Xiong; Shi, Jun-Li; Ma, Wen-Juan; Li, Yong; Ye, Yan-Fang; Liang, Hu; Ke, Liang-Ru; Lv, Xing; Yang, Jing; Xiang, Yan-Qun; Guo, Xiang
2016-06-29
For patients with nasopharyngeal carcinoma (NPC) who undergo re-irradiation with intensity-modulated radiotherapy (IMRT), lethal nasopharyngeal necrosis (LNN) is a severe late adverse event. The purpose of this study was to identify risk factors for LNN and develop a model to predict LNN after radical re-irradiation with IMRT in patients with recurrent NPC. Patients who underwent radical re-irradiation with IMRT for locally recurrent NPC between March 2001 and December 2011 and who had no evidence of distant metastasis were included in this study. Clinical characteristics, including recurrent carcinoma conditions and dosimetric features, were evaluated as candidate risk factors for LNN. Logistic regression analysis was used to identify independent risk factors and construct the predictive scoring model. Among 228 patients enrolled in this study, 204 were at risk of developing LNN based on risk analysis. Of the 204 patients treated, 31 (15.2%) developed LNN. Logistic regression analysis showed that female sex (P = 0.008), necrosis before re-irradiation (P = 0.008), accumulated total prescription dose to the gross tumor volume (GTV) ≥145.5 Gy (P = 0.043), and recurrent tumor volume ≥25.38 cm(3) (P = 0.009) were independent risk factors for LNN. A model to predict LNN was then constructed that included these four independent risk factors. A model that includes sex, necrosis before re-irradiation, accumulated total prescription dose to GTV, and recurrent tumor volume can effectively predict the risk of developing LNN in NPC patients who undergo radical re-irradiation with IMRT.
Factors predictive of risk for complications in patients with oesophageal foreign bodies.
Sung, Sang Hun; Jeon, Seong Woo; Son, Hyuk Su; Kim, Sung Kook; Jung, Min Kyu; Cho, Chang Min; Tak, Won Young; Kweon, Young Oh
2011-08-01
Reports on predictive risk factors associated with complications of ingested oesophageal foreign bodies are rare. The aim of this study was to determine the predictive risk factors associated with the complications of oesophageal foreign bodies. Three hundred sixteen cases with foreign bodies in the oesophagus were retrospectively investigated. The predictive risk factors for complications after foreign body ingestion were analysed by multivariate logistic regression, and included age, size and type of foreign body ingested, duration of impaction, and the level of foreign body impaction. The types of oesophageal foreign bodies included fish bones (37.0%), food (19.0%), and metals (18.4%). The complications associated with foreign bodies were ulcers (21.2%), lacerations (14.9%), erosions (12.0%), and perforation (1.9%). Multivariate analysis showed that the duration of impaction (p<0.001), and the type (p<0.001) and size of the foreign bodies (p<0.001) were significant independent risk factors associated with the development of complications in patients with oesophageal foreign bodies. In patients with oesophageal foreign bodies, the risk of complications was increased with a longer duration of impaction, bone type, and larger size. Copyright © 2011 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.
Lansaat, Liset; van der Noort, Vincent; Bernard, Simone E; Eerenstein, Simone E J; Plaat, Boudewijn E C; Langeveld, Ton A P M; Lacko, Martin; Hilgers, Frans J M; de Bree, Remco; Takes, Robert P; van den Brekel, Michiel W M
2018-03-01
Incidences of pharyngocutaneous fistulization (PCF) after total laryngectomy (TL) reported in the literature vary widely, ranging from 2.6 to 65.5%. Comparison between different centers might identify risk factors, but also might enable improvements in quality of care. To enable this on a national level, an audit in the 8 principle Dutch Head and Neck Centers (DHNC) was initiated. A retrospective chart review of all 324 patients undergoing laryngectomy in a 2-year (2012 and 2013) period was performed. Overall PCF%, PCF% per center and factors predictive for PCF were identified. Furthermore, a prognostic model predicting the PCF% per center was developed. To provide additional data, a survey among the head and neck surgeons of the participating centers was carried out. Overall PCF% was 25.9. The multivariable prediction model revealed that previous treatment with (chemo)radiotherapy in combination with a long interval between primary treatment and TL, previous tracheotomy, near total pharyngectomy, neck dissection, and BMI < 18 were the best predictors for PCF. Early oral intake did not influence PCF rate. PCF% varied quite widely between centers, but for a large extend this could be explained with the prediction model. PCF performance rate (difference between the PCF% and the predicted PCF%) per DHNC, though, shows that not all differences are explained by factors established in the prediction model. However, these factors explain enough of the differences that, compensating for these factors, hospital is no longer independently predictive for PCF. This nationwide audit has provided valid comparative PCF data confirming the known risk factors from the literature which are important for counseling on PCF risks. Data show that variations in PCF% in the DHNCs (in part) are explainable by the variations in these predictive factors. Since elective neck dissection is a major risk factor for PCF, it only should be performed on well funded indication.
Percent Mammographic Density and Dense Area as Risk Factors for Breast Cancer.
Rauh, C; Hack, C C; Häberle, L; Hein, A; Engel, A; Schrauder, M G; Fasching, P A; Jud, S M; Ekici, A B; Loehberg, C R; Meier-Meitinger, M; Ozan, S; Schulz-Wendtland, R; Uder, M; Hartmann, A; Wachter, D L; Beckmann, M W; Heusinger, K
2012-08-01
Purpose: Mammographic characteristics are known to be correlated to breast cancer risk. Percent mammographic density (PMD), as assessed by computer-assisted methods, is an established risk factor for breast cancer. Along with this assessment the absolute dense area (DA) of the breast is reported as well. Aim of this study was to assess the predictive value of DA concerning breast cancer risk in addition to other risk factors and in addition to PMD. Methods: We conducted a case control study with hospital-based patients with a diagnosis of invasive breast cancer and healthy women as controls. A total of 561 patients and 376 controls with available mammographic density were included into this study. We describe the differences concerning the common risk factors BMI, parital status, use of hormone replacement therapy (HRT) and menopause between cases and controls and estimate the odds ratios for PMD and DA, adjusted for the mentioned risk factors. Furthermore we compare the prediction models with each other to find out whether the addition of DA improves the model. Results: Mammographic density and DA were highly correlated with each other. Both variables were as well correlated to the commonly known risk factors with an expected direction and strength, however PMD (ρ = -0.56) was stronger correlated to BMI than DA (ρ = -0.11). The group of women within the highest quartil of PMD had an OR of 2.12 (95 % CI: 1.25-3.62). This could not be seen for the fourth quartile concerning DA. However the assessment of breast cancer risk could be improved by including DA in a prediction model in addition to common risk factors and PMD. Conclusions: The inclusion of the parameter DA into a prediction model for breast cancer in addition to established risk factors and PMD could improve the breast cancer risk assessment. As DA is measured together with PMD in the process of computer-assisted assessment of PMD it might be considered to include it as one additional breast cancer risk factor that is obtained from breast imaging.
Vuong, Kylie; Armstrong, Bruce K; Weiderpass, Elisabete; Lund, Eiliv; Adami, Hans-Olov; Veierod, Marit B; Barrett, Jennifer H; Davies, John R; Bishop, D Timothy; Whiteman, David C; Olsen, Catherine M; Hopper, John L; Mann, Graham J; Cust, Anne E; McGeechan, Kevin
2016-08-01
Identifying individuals at high risk of melanoma can optimize primary and secondary prevention strategies. To develop and externally validate a risk prediction model for incident first-primary cutaneous melanoma using self-assessed risk factors. We used unconditional logistic regression to develop a multivariable risk prediction model. Relative risk estimates from the model were combined with Australian melanoma incidence and competing mortality rates to obtain absolute risk estimates. A risk prediction model was developed using the Australian Melanoma Family Study (629 cases and 535 controls) and externally validated using 4 independent population-based studies: the Western Australia Melanoma Study (511 case-control pairs), Leeds Melanoma Case-Control Study (960 cases and 513 controls), Epigene-QSkin Study (44 544, of which 766 with melanoma), and Swedish Women's Lifestyle and Health Cohort Study (49 259 women, of which 273 had melanoma). We validated model performance internally and externally by assessing discrimination using the area under the receiver operating curve (AUC). Additionally, using the Swedish Women's Lifestyle and Health Cohort Study, we assessed model calibration and clinical usefulness. The risk prediction model included hair color, nevus density, first-degree family history of melanoma, previous nonmelanoma skin cancer, and lifetime sunbed use. On internal validation, the AUC was 0.70 (95% CI, 0.67-0.73). On external validation, the AUC was 0.66 (95% CI, 0.63-0.69) in the Western Australia Melanoma Study, 0.67 (95% CI, 0.65-0.70) in the Leeds Melanoma Case-Control Study, 0.64 (95% CI, 0.62-0.66) in the Epigene-QSkin Study, and 0.63 (95% CI, 0.60-0.67) in the Swedish Women's Lifestyle and Health Cohort Study. Model calibration showed close agreement between predicted and observed numbers of incident melanomas across all deciles of predicted risk. In the external validation setting, there was higher net benefit when using the risk prediction model to classify individuals as high risk compared with classifying all individuals as high risk. The melanoma risk prediction model performs well and may be useful in prevention interventions reliant on a risk assessment using self-assessed risk factors.
Childhood Risk Factors for Lifetime Anorexia Nervosa by Age 30 Years in a National Birth Cohort
ERIC Educational Resources Information Center
Nicholls, Dasha E.; Viner, Russell M.
2009-01-01
Whether previously identified childhood risk factors for anorexia nervosa (AN) predict self-reported lifetime AN by age 30 is examined. The cohort confirmed four risk and two protective factors out of the 22 suggested risk factors. The study used data from the 1970 British Cohort Study.
High serum total cholesterol is a long-term cause of osteoporotic fracture.
Trimpou, P; Odén, A; Simonsson, T; Wilhelmsen, L; Landin-Wilhelmsen, K
2011-05-01
Risk factors for osteoporotic fractures were evaluated in 1,396 men and women for a period of 20 years. Serum total cholesterol was found to be an independent osteoporotic fracture risk factor whose predictive power improves with time. The purpose of this study was to evaluate long-term risk factors for osteoporotic fracture. A population random sample of men and women aged 25-64 years (the Gothenburg WHO MONICA project, N = 1,396, 53% women) was studied prospectively. The 1985 baseline examination recorded physical activity at work and during leisure time, psychological stress, smoking habits, coffee consumption, BMI, waist/hip ratio, blood pressure, total, HDL and LDL cholesterol, triglycerides, and fibrinogen. Osteoporotic fractures over a period of 20 years were retrieved from the Gothenburg hospital registers. Poisson regression was used to analyze the predictive power for osteoporotic fracture of each risk factor. A total number of 258 osteoporotic fractures occurred in 143 participants (10.2%). As expected, we found that previous fracture, smoking, coffee consumption, and lower BMI each increase the risk for osteoporotic fracture independently of age and sex. More unexpectedly, we found that the gradient of risk of serum total cholesterol to predict osteoporotic fracture significantly increases over time (p = 0.0377). Serum total cholesterol is an independent osteoporotic fracture risk factor whose predictive power improves with time. High serum total cholesterol is a long-term cause of osteoporotic fracture.
Biological risk factors for suicidal behaviors: a meta-analysis
Chang, B P; Franklin, J C; Ribeiro, J D; Fox, K R; Bentley, K H; Kleiman, E M; Nock, M K
2016-01-01
Prior studies have proposed a wide range of potential biological risk factors for future suicidal behaviors. Although strong evidence exists for biological correlates of suicidal behaviors, it remains unclear if these correlates are also risk factors for suicidal behaviors. We performed a meta-analysis to integrate the existing literature on biological risk factors for suicidal behaviors and to determine their statistical significance. We conducted a systematic search of PubMed, PsycInfo and Google Scholar for studies that used a biological factor to predict either suicide attempt or death by suicide. Inclusion criteria included studies with at least one longitudinal analysis using a biological factor to predict either of these outcomes in any population through 2015. From an initial screen of 2541 studies we identified 94 cases. Random effects models were used for both meta-analyses and meta-regression. The combined effect of biological factors produced statistically significant but relatively weak prediction of suicide attempts (weighted mean odds ratio (wOR)=1.41; CI: 1.09–1.81) and suicide death (wOR=1.28; CI: 1.13–1.45). After accounting for publication bias, prediction was nonsignificant for both suicide attempts and suicide death. Only two factors remained significant after accounting for publication bias—cytokines (wOR=2.87; CI: 1.40–5.93) and low levels of fish oil nutrients (wOR=1.09; CI: 1.01–1.19). Our meta-analysis revealed that currently known biological factors are weak predictors of future suicidal behaviors. This conclusion should be interpreted within the context of the limitations of the existing literature, including long follow-up intervals and a lack of tests of interactions with other risk factors. Future studies addressing these limitations may more effectively test for potential biological risk factors. PMID:27622931
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhong, Bin-Yan; He, Shi-Cheng; Zhu, Hai-Dong
PurposeWe aim to determine the predictors of new adjacent vertebral fractures (AVCFs) after percutaneous vertebroplasty (PVP) in patients with osteoporotic vertebral compression fractures (OVCFs) and to construct a risk prediction score to estimate a 2-year new AVCF risk-by-risk factor condition.Materials and MethodsPatients with OVCFs who underwent their first PVP between December 2006 and December 2013 at Hospital A (training cohort) and Hospital B (validation cohort) were included in this study. In training cohort, we assessed the independent risk predictors and developed the probability of new adjacent OVCFs (PNAV) score system using the Cox proportional hazard regression analysis. The accuracy ofmore » this system was then validated in both training and validation cohorts by concordance (c) statistic.Results421 patients (training cohort: n = 256; validation cohort: n = 165) were included in this study. In training cohort, new AVCFs after the first PVP treatment occurred in 33 (12.9%) patients. The independent risk factors were intradiscal cement leakage and preexisting old vertebral compression fracture(s). The estimated 2-year absolute risk of new AVCFs ranged from less than 4% in patients with neither independent risk factors to more than 45% in individuals with both factors.ConclusionsThe PNAV score is an objective and easy approach to predict the risk of new AVCFs.« less
L'Italien, G; Ford, I; Norrie, J; LaPuerta, P; Ehreth, J; Jackson, J; Shepherd, J
2000-03-15
The clinical decision to treat hypercholesterolemia is premised on an awareness of patient risk, and cardiac risk prediction models offer a practical means of determining such risk. However, these models are based on observational cohorts where estimates of the treatment benefit are largely inferred. The West of Scotland Coronary Prevention Study (WOSCOPS) provides an opportunity to develop a risk-benefit prediction model from the actual observed primary event reduction seen in the trial. Five-year Cox model risk estimates were derived from all WOSCOPS subjects (n = 6,595 men, aged 45 to 64 years old at baseline) using factors previously shown to be predictive of definite fatal coronary heart disease or nonfatal myocardial infarction. Model risk factors included age, diastolic blood pressure, total cholesterol/ high-density lipoprotein ratio (TC/HDL), current smoking, diabetes, family history of fatal coronary heart disease, nitrate use or angina, and treatment (placebo/ 40-mg pravastatin). All risk factors were expressed as categorical variables to facilitate risk assessment. Risk estimates were incorporated into a simple, hand-held slide rule or risk tool. Risk estimates were identified for 5-year age bands (45 to 65 years), 4 categories of TC/HDL ratio (<5.5, 5.5 to <6.5, 6.5 to <7.5, > or = 7.5), 2 levels of diastolic blood pressure (<90, > or = 90 mm Hg), from 0 to 3 additional risk factors (current smoking, diabetes, family history of premature fatal coronary heart disease, nitrate use or angina), and pravastatin treatment. Five-year risk estimates ranged from 2% in very low-risk subjects to 61% in the very high-risk subjects. Risk reduction due to pravastatin treatment averaged 31%. Thus, the Cardiovascular Event Reduction Tool (CERT) is a risk prediction model derived from the WOSCOPS trial. Its use will help physicians identify patients who will benefit from cholesterol reduction.
Use of clinical risk factors to identify postmenopausal women with vertebral fractures.
Tobias, J H; Hutchinson, A P; Hunt, L P; McCloskey, E V; Stone, M D; Martin, J C; Thompson, P W; Palferman, T G; Bhalla, A K
2007-01-01
Previous studies have been unable to identify risk factors for prevalent vertebral fractures (VF), which are suitable for use in selection strategies intended to target high-risk sub-groups for diagnostic assessment. However, these studies generally consisted of large epidemiology surveys based on questionnaires and were only able to evaluate a limited number of risk factors. Here, we investigated whether a stronger relationship exists with prevalent VF when conventional risk factors are combined with additional information obtained from detailed one-to-one assessment. Women aged 65-75 registered at four geographically distinct GP practices were invited to participate (n=1,518), of whom 540 attended for assessment as follows: a questionnaire asking about risk factors for osteoporosis such as height loss compared to age 25 and history of non-vertebral fracture (NVF), the get-up-and-go test, Margolis back pain score, measurement of wall-tragus and rib-pelvis distances, and BMD as measured by the distal forearm BMD. A lateral thoraco-lumbar spine X-ray was obtained, which was subsequently scored for the presence of significant vertebral deformities. Of the 509 subjects who underwent spinal radiographs, 37 (7.3%) were found to have one or more VF. Following logistic regression analysis, the four most predictive clinical risk factors for prevalent VF were: height loss (P=0.006), past NVF (P=0.004), history of back pain (P=0.075) and age (P=0.05). BMD was also significantly associated with prevalent VF (P=0.002), but its inclusion did not affect associations with other variables. Factors elicited from detailed one-to-one assessment were not related to the risk of one or more prevalent VFs. The area under ROC curves derived from these regressions, which suggested that models for prevalent VF had modest predictive accuracy, were as follows: 0.68 (BMD), 0.74 (four clinical risk factors above) and 0.78 (clinical risk factors + BMD). Analyses were repeated in relation to the subgroup of 13 patients with two or more VFs, which revealed that in this instance, the Margolis back pain score and rib-pelvis distance were associated with the presence of multiple VFs (P=0.022 and 0.026, respectively). Moreover, the predictive value as reflected by the ROC curve area was improved: 0.80 (BMD), 0.88 (the four most predictive clinical risk factors consisting of the height loss, past NVF, Margolis back pain score and rib-pelvis distance) and 0.91 (clinical risk factors + BMD). Evaluation of additional risk factors from detailed one-to-one assessment does not improve the predictive value of risk factors for one or more prevalent vertebral deformities in postmenopausal women. However, the use of factors such as the Margolis back pain score and rib-pelvis distance may be helpful in identifying postmenopausal women at high risk of multiple prevalent VFs.
Ditmyer, Marcia M; Dounis, Georgia; Howard, Katherine M; Mobley, Connie; Cappelli, David
2011-05-20
The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting. This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model. Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%. Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.
Predictive factors for poor prognosis febrile neutropenia.
Ahn, Shin; Lee, Yoon-Seon
2012-07-01
Most patients with chemotherapy-induced febrile neutropenia recover rapidly without serious complications. However, it still remains a life-threatening treatment-related toxicity, and is associated with dose reductions and delays of chemotherapeutic agents that may compromise treatment outcomes. Recent developments of risk stratification enabled early discharge with oral antibiotics for low-risk patients. However, even in low-risk patients, medical complications including bacteremia could happen. The authors reviewed recent literature to provide an update on research regarding predictive factors for poor prognosis in patients with febrile neutropenia. Various prognostic factors have been suggested with controversies. Hematological parameters, prophylactic measurements and patient-specific risk factors showed inconsistent results. MASCC risk-index score, which was originally developed to identify low-risk patients, in turn showed that the lower the MASCC score, the poorer the prognosis of febrile neutropenia, with very low levels (<15), the rate of complications was high. Patients with severe sepsis and septic shock commonly had procalcitonin concentration above 2.0 ng/ml, and this level should be considered at high risk of poor prognosis. Lower MASCC score and higher procalcitonin concentration can predict poor outcomes in febrile neutropenia. More research is required with regard to the other factors showing controversies.
Davis, Cynthia R; Dearing, Eric; Usher, Nicole; Trifiletti, Sarah; Zaichenko, Lesya; Ollen, Elizabeth; Brinkoetter, Mary T; Crowell-Doom, Cindy; Joung, Kyoung; Park, Kyung Hee; Mantzoros, Christos S; Crowell, Judith A
2014-02-01
This study examined whether a novel indicator of overall childhood adversity, incorporating number of adversities, severity, and chronicity, predicted central obesity beyond contributions of "modifiable" risk factors including psychosocial characteristics and health behaviors in a diverse sample of midlife adults. The study also examined whether the overall adversity score (number of adversities × severity × chronicity) better predicted obesity compared to cumulative adversity (number of adversities), a more traditional assessment of childhood adversity. 210 Black/African Americans and White/European Americans, mean age=45.8; ±3.3 years, were studied cross-sectionally. Regression analysis examined overall childhood adversity as a direct, non-modifiable risk factor for central obesity (waist-hip ratio) and body mass index (BMI), with and without adjustment for established adult psychosocial risk factors (education, employment, social functioning) and heath behavior risk factors (smoking, drinking, diet, exercise). Overall childhood adversity was an independent significant predictor of central obesity, and the relations between psychosocial and health risk factors and central obesity were not significant when overall adversity was in the model. Overall adversity was not a statistically significant predictor of BMI. Overall childhood adversity, incorporating severity and chronicity and cumulative scores, predicts central obesity beyond more contemporaneous risk factors often considered modifiable. This is consistent with early dysregulation of metabolic functioning. Findings can inform practitioners interested in the impact of childhood adversity and personalizing treatment approaches of obesity within high-risk populations. Prevention/intervention research is necessary to discover and address the underlying causes and impact of childhood adversity on metabolic functioning. © 2013.
Fibrinogen concentration and its role in CVD risk in black South Africans--effect of urbanisation.
Pieters, Marlien; de Maat, Moniek P M; Jerling, Johann C; Hoekstra, Tiny; Kruger, Annamarie
2011-09-01
The aim of this study was to investigate correlates of fibrinogen concentration in black South Africans, as well as its association with cardiovascular disease (CVD) risk and whether urbanisation influences this association. A total of 1,006 rural and 1,004 urban black South Africans from the PURE study were cross-sectionally analysed. The association of fibrinogen with CVD risk was determined by investigating the association of fibrinogen with other CVD risk markers as well as with predicted CVD risk using the Reynolds Risk score. The rural group had a significantly higher fibrinogen concentration than the urban group, despite higher levels of risk factors and increased predicted CVD risk in the urban group. Increased levels of CVD risk factors were, however, still associated with increased fibrinogen concentration. Fibrinogen correlated significantly, but weakly, with overall predicted CVD risk. This correlation was stronger in the urban than in the rural group. Multiple regression analysis showed that a smaller percentage of the variance in fibrinogen is explained by the traditional CVD risk factors in the rural than in the urban group. In conclusion, fibrinogen is weakly associated with CVD risk (predicted overall risk as well with individual risk factors) in black South Africans, and is related to the degree of urbanisation. Increased fibrinogen concentration, in black South Africans, especially in rural areas, is largely unexplained, and likely not strongly correlated with traditional CVD-related lifestyle and pathophysiological processes. This does, however, not exclude the possibility that once increased, the fibrinogen concentration contributes to future development of CVD.
Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na
2016-11-23
A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P < 0.001). Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.
Maselko, Joanna; Bates, Lisa M; Avendaño, Mauricio; Glymour, M Maria
2009-12-01
To examine the role of sex and marital status in the distribution and consequences of cardiovascular risk factors for stroke. Longitudinal cohort. U.S. national sample, community based. U.S. adults aged 50 and older and their spouses. Health and Retirement Study (HRS) participants born between 1900 and 1947 (N=22,818), aged 50 and older, and stroke-free at baseline were followed an average of 9.4 years for self- or proxy-reported stroke (2,372 events). Financial resources, behavioral risk factors, and cardiovascular conditions were used to predict incident stroke in Cox proportional hazard models stratified according to sex and marital status (married, widowed, divorced or separated, or never married). Women were less likely to be married than men. The distribution of risk factors differed according to sex and marital status. Men had higher incident stroke rates than women, even after full risk factor adjustment (hazard ratio (HR)=1.22, 95% confidence interval (CI)=1.11-1.34). For both sexes, being never married or widowed predicted greater risk, associations that were attenuated after adjustment for financial resources. Widowed men had the highest risk (HR=1.40, 95% CI=1.12-1.74 vs married women). Lower income and wealth were associated with similarly high risk across subgroups, although this risk factor especially affected unmarried women, with this group reporting the lowest income and wealth levels. Most other risk factors had similar HRs across subgroups, although moderate alcohol use did not predict lower stroke risk in unmarried women. Stroke incidence and risk factors vary substantially according to sex and marital status. It is likely that gendered social experiences, such as marriage and socioeconomic disadvantage, mediate pathways linking sex and stroke.
Padmanabhan, Jaya L; Shah, Jai L; Tandon, Neeraj; Keshavan, Matcheri S
2017-03-01
Young relatives of individuals with schizophrenia (i.e. youth at familial high-risk, FHR) are at increased risk of developing psychotic disorders, and show higher rates of psychiatric symptoms, cognitive and neurobiological abnormalities than non-relatives. It is not known whether overall exposure to environmental risk factors increases risk of conversion to psychosis in FHR subjects. Subjects consisted of a pilot longitudinal sample of 83 young FHR subjects. As a proof of principle, we examined whether an aggregate score of exposure to environmental risk factors, which we term a 'polyenviromic risk score' (PERS), could predict conversion to psychosis. The PERS combines known environmental risk factors including cannabis use, urbanicity, season of birth, paternal age, obstetric and perinatal complications, and various types of childhood adversity, each weighted by its odds ratio for association with psychosis in the literature. A higher PERS was significantly associated with conversion to psychosis in young, familial high-risk subjects (OR=1.97, p=0.009). A model combining the PERS and clinical predictors had a sensitivity of 27% and specificity of 96%. An aggregate index of environmental risk may help predict conversion to psychosis in FHR subjects. Copyright © 2016 Elsevier B.V. All rights reserved.
Can shoulder dystocia be reliably predicted?
Dodd, Jodie M; Catcheside, Britt; Scheil, Wendy
2012-06-01
To evaluate factors reported to increase the risk of shoulder dystocia, and to evaluate their predictive value at a population level. The South Australian Pregnancy Outcome Unit's population database from 2005 to 2010 was accessed to determine the occurrence of shoulder dystocia in addition to reported risk factors, including age, parity, self-reported ethnicity, presence of diabetes and infant birth weight. Odds ratios (and 95% confidence interval) of shoulder dystocia was calculated for each risk factor, which were then incorporated into a logistic regression model. Test characteristics for each variable in predicting shoulder dystocia were calculated. As a proportion of all births, the reported rate of shoulder dystocia increased significantly from 0.95% in 2005 to 1.38% in 2010 (P = 0.0002). Using a logistic regression model, induction of labour and infant birth weight greater than both 4000 and 4500 g were identified as significant independent predictors of shoulder dystocia. The value of risk factors alone and when incorporated into the logistic regression model was poorly predictive of the occurrence of shoulder dystocia. While there are a number of factors associated with an increased risk of shoulder dystocia, none are of sufficient sensitivity or positive predictive value to allow their use clinically to reliably and accurately identify the occurrence of shoulder dystocia. © 2012 The Authors ANZJOG © 2012 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.
de Wouters, Solange; Daxhelet, Jérémy; Kaminski, Ludovic; Thienpont, Emmanuel; Cornu, Olivier; Yombi, Jean Cyr
2015-12-01
Methicillin-Resistant Staphylococcus Aureus (MRSA) has been widely recognized as a serious problem in hospital settings. The purpose of this study is to evaluate the predictive value of MRSA colonization factors in the detection of MRSA carriers in an orthopedic ward. A systematic MRSA detection strategy was set up to assess the predictive value of MRSA colonization factors among 554 patients undergoing elective knee arthroplasty. In total 116 patients were found positive for Staphylococcus Aureus; among those 110/116 patients were found positive for Methicillin-Sensitive Staphylococcus Aureus (MSSA) and 6/116 for MRSA. Only one patient out of six presented two risk factors according to MRSA risk factors. In this study, no correlation was found between the remaining conventional risk factors, according to Belgian guidelines, defined to target high-risk populations and to identify MRSA carriers. Established criteria for selective MRSA screening do not allow detecting MRSA carriers. The objective of detecting MRSA carriers is not correctly met by the actual applied criteria (Belgian consensus) for a selective screening policy. Future studies should aim at identifying the right risk factors, depending of the country's prevalence of MRSA, to improve the ability to predict the risk of MRSA carriage at hospital admission.
Gender differences in predicting high-risk drinking among undergraduate students.
Wilke, Dina J; Siebert, Darcy Clay; Delva, Jorge; Smith, Michael P; Howell, Richard L
2005-01-01
The purpose of this study was to examine gender differences in college students' high-risk drinking as measured by an estimated blood alcohol concentration (eBAC) based on gender, height, weight, self-reported number of drinks, and hours spent drinking. Using a developmental/contextual framework, high-risk drinking is conceptualized as a function of relevant individual characteristics, interpersonal factors, and contextual factors regularly mentioned in the college drinking literature. Individual characteristics include race, gender, and age; interpersonal characteristics include number of sexual partners and having experienced forced sexual contact. Finally, contextual factors include Greek membership, living off-campus, and perception of peer drinking behavior. This study is a secondary data analysis of 1,422 students at a large university in the Southeast. Data were gathered from a probability sample of students through a mail survey. A three-step hierarchical logistic regression analysis showed gender differences in the pathway for high-risk drinking. For men, high-risk drinking was predicted by a combination of individual characteristics and contextual factors. For women, interpersonal factors, along with individual characteristics and contextual factors, predicted high-risk drinking, highlighting the importance of understanding female sexual relationships and raising questions about women's risk-taking behavior. Implications for prevention and assessment are discussed.
Sacco, Ralph L.; Khatri, Minesh; Rundek, Tatjana; Xu, Qiang; Gardener, Hannah; Boden-Albala, Bernadette; Di Tullio, Marco R.; Homma, Shunichi; Elkind, Mitchell SV; Paik, Myunghee C
2010-01-01
Objective To improve global vascular risk prediction with behavioral and anthropometric factors. Background Few cardiovascular risk models are designed to predict the global vascular risk of MI, stroke, or vascular death in multi-ethnic individuals, and existing schemes do not fully include behavioral risk factors. Methods A randomly-derived, population-based, prospective cohort of 2737 community participants free of stroke and coronary artery disease were followed annually for a median of 9.0 years in the Northern Manhattan Study (mean age 69 years; 63.2% women; 52.7% Hispanic, 24.9% African-American, 19.9% white). A global vascular risk score (GVRS) predictive of stroke, myocardial infarction, or vascular death was developed by adding variables to the traditional Framingham cardiovascular variables based on the likelihood ratio criterion. Model utility was assessed through receiver operating characteristics, calibration, and effect on reclassification of subjects. Results Variables which significantly added to the traditional Framingham profile included waist circumference, alcohol consumption, and physical activity. Continuous measures for blood pressure and fasting blood sugar were used instead of hypertension and diabetes. Ten -year event-free probabilities were 0.95 for the first quartile of GVRS, 0.89 for the second quartile, 0.79 for the third quartile, and 0.56 for the fourth quartile. The addition of behavioral factors in our model improved prediction of 10 -year event rates compared to a model restricted to the traditional variables. Conclusion A global vascular risk score that combines both traditional, behavioral, and anthropometric risk factors, uses continuous variables for physiological parameters, and is applicable to non-white subjects could improve primary prevention strategies. PMID:19958966
High-sensitive factor I and C-reactive protein based biomarkers for coronary artery disease.
Zhao, Qing; Du, Jian-Shi; Han, Dong-Mei; Ma, Ying
2014-01-01
An analysis of high-sensitive factor I and C-reactive proteins as biomarkers for coronary artery disease has been performed from 19 anticipated cohort studies that included 21,567 participants having no information about coronary artery disease. Besides, the clinical implications of statin therapy initiated due to assessment of factor I and C-reactive proteins have also been modeled during studies. The measure of risk discrimination (C-index) was increased (by 0.0101) as per the prognostic model for coronary artery disease with respect to sex, smoking status, age, blood pressure, total cholesterol level along with diabetic history characteristic parameters. The C-index was further raised by 0.0045 and 0.0053 when factor I and C-reactive proteins based information were added, respectively which finally predicted 10-year risk categories as: high (> 20%), medium (10% to < 20%), and low (< 10%) risks. We found 2,254 persons (among 15,000 adults (age ≥ 45 years)) would initially be classified as being at medium risk for coronary artery disease when only conventional risk factors were used as calculated risk. Besides, persons with a predicted risk of more than 20% as well as for persons suffering from other risk factors (i.e. diabetes), statin therapy was initiated (irrespective of their decade old predicted risk). We conclude that under current treatment guidelines assessment of factor I and C-reactive proteins levels (as biomarker) in people at medium risk for coronary artery disease could prevent one additional coronary artery disease risk over a period a decade for every 390-500 people screened.
Arthur, Michael W.; Brown, Eric C.; Briney, John S.; Hawkins, J. David; Abbott, Robert D.; Catalano, Richard F.; Becker, Linda; Langer, Michael; Mueller, Martin T.
2016-01-01
BACKGROUND School administrators and teachers face difficult decisions about how best to use school resources in order to meet academic achievement goals. Many are hesitant to adopt prevention curricula that are not focused directly on academic achievement. Yet, some have hypothesized that prevention curricula can remove barriers to learning and, thus, promote achievement. This study examined relationships between school levels of student substance use and risk and protective factors that predict adolescent problem behaviors and achievement test performance in Washington State. METHODS Hierarchical Generalized Linear Models were used to examine predictive associations between school-averaged levels of substance use and risk and protective factors and Washington State students’ likelihood of meeting achievement test standards on the Washington Assessment of Student Learning, statistically controlling for demographic and economic factors known to be associated with achievement. RESULTS Results indicate that levels of substance use and risk/protective factors predicted the academic test score performance of students. Many of these effects remained significant even after controlling for model covariates. CONCLUSIONS The findings suggest that implementing prevention programs that target empirically identified risk and protective factors have the potential to positively affect students’ academic achievement. PMID:26149305
Meads, Catherine; Ahmed, Ikhlaaq; Riley, Richard D
2012-04-01
A risk prediction model is a statistical tool for estimating the probability that a currently healthy individual with specific risk factors will develop a condition in the future such as breast cancer. Reliably accurate prediction models can inform future disease burdens, health policies and individual decisions. Breast cancer prediction models containing modifiable risk factors, such as alcohol consumption, BMI or weight, condom use, exogenous hormone use and physical activity, are of particular interest to women who might be considering how to reduce their risk of breast cancer and clinicians developing health policies to reduce population incidence rates. We performed a systematic review to identify and evaluate the performance of prediction models for breast cancer that contain modifiable factors. A protocol was developed and a sensitive search in databases including MEDLINE and EMBASE was conducted in June 2010. Extensive use was made of reference lists. Included were any articles proposing or validating a breast cancer prediction model in a general female population, with no language restrictions. Duplicate data extraction and quality assessment were conducted. Results were summarised qualitatively, and where possible meta-analysis of model performance statistics was undertaken. The systematic review found 17 breast cancer models, each containing a different but often overlapping set of modifiable and other risk factors, combined with an estimated baseline risk that was also often different. Quality of reporting was generally poor, with characteristics of included participants and fitted model results often missing. Only four models received independent validation in external data, most notably the 'Gail 2' model with 12 validations. None of the models demonstrated consistently outstanding ability to accurately discriminate between those who did and those who did not develop breast cancer. For example, random-effects meta-analyses of the performance of the 'Gail 2' model showed the average C statistic was 0.63 (95% CI 0.59-0.67), and the expected/observed ratio of events varied considerably across studies (95% prediction interval for E/O ratio when the model was applied in practice was 0.75-1.19). There is a need for models with better predictive performance but, given the large amount of work already conducted, further improvement of existing models based on conventional risk factors is perhaps unlikely. Research to identify new risk factors with large additionally predictive ability is therefore needed, alongside clearer reporting and continual validation of new models as they develop.
Coronary Risk Factor Scoring as a Guide for Counseling
NASA Technical Reports Server (NTRS)
Fleck, R. L.
1971-01-01
A risk factor scoring system for early detection, possible prediction, and counseling to coronary heart disease patients is discussed. Scoring data include dynamic EKG, cholesterol levels, triglycerine content, total lipid level, total phospolipid levels, and electrophoretic patterns. Results indicate such a system is effective in identifying high risk subjects, but that the ability to predict exceeds the ability to prevent heart disease or its complications.
Putative Risk Factors in Developmental Dyslexia: A Case-Control Study of Italian Children
ERIC Educational Resources Information Center
Mascheretti, Sara; Marino, Cecilia; Simone, Daniela; Quadrelli, Ermanno; Riva, Valentina; Cellino, Maria Rosaria; Maziade, Michel; Brombin, Chiara; Battaglia, Marco
2015-01-01
Although dyslexia runs in families, several putative risk factors that cannot be immediately identified as genetic predict reading disability. Published studies analyzed one or a few risk factors at a time, with relatively inconsistent results. To assess the contribution of several putative risk factors to the development of dyslexia, we conducted…
Making predictions of mangrove deforestation: a comparison of two methods in Kenya.
Rideout, Alasdair J R; Joshi, Neha P; Viergever, Karin M; Huxham, Mark; Briers, Robert A
2013-11-01
Deforestation of mangroves is of global concern given their importance for carbon storage, biogeochemical cycling and the provision of other ecosystem services, but the links between rates of loss and potential drivers or risk factors are rarely evaluated. Here, we identified key drivers of mangrove loss in Kenya and compared two different approaches to predicting risk. Risk factors tested included various possible predictors of anthropogenic deforestation, related to population, suitability for land use change and accessibility. Two approaches were taken to modelling risk; a quantitative statistical approach and a qualitative categorical ranking approach. A quantitative model linking rates of loss to risk factors was constructed based on generalized least squares regression and using mangrove loss data from 1992 to 2000. Population density, soil type and proximity to roads were the most important predictors. In order to validate this model it was used to generate a map of losses of Kenyan mangroves predicted to have occurred between 2000 and 2010. The qualitative categorical model was constructed using data from the same selection of variables, with the coincidence of different risk factors in particular mangrove areas used in an additive manner to create a relative risk index which was then mapped. Quantitative predictions of loss were significantly correlated with the actual loss of mangroves between 2000 and 2010 and the categorical risk index values were also highly correlated with the quantitative predictions. Hence, in this case the relatively simple categorical modelling approach was of similar predictive value to the more complex quantitative model of mangrove deforestation. The advantages and disadvantages of each approach are discussed, and the implications for mangroves are outlined. © 2013 Blackwell Publishing Ltd.
Smith, Ann; Patterson, Chris; Yarnell, John; Rumley, Ann; Ben-Shlomo, Yoav; Lowe, Gordon
2005-11-15
Few studies have examined whether hemostatic markers contribute to risk of coronary disease and ischemic stroke independently of conventional risk factors. This study examines 11 hemostatic markers that reflect different aspects of the coagulation process to determine which have prognostic value after accounting for conventional risk factors. A total of 2398 men aged 49 to 65 years were examined in 1984 to 1988, and the majority gave a fasting blood sample for assay of lipids and hemostatic markers. Men were followed up for a median of 13 years, and cardiovascular disease (CVD) events were recorded. There were 486 CVD events in total, 353 with prospective coronary disease and 133 with prospective ischemic stroke. On univariable analysis, fibrinogen, low activated protein C ratio, D-dimer, tissue plasminogen activator (tPA), and plasminogen activator inhibitor-1 (PAI-1) were associated significantly with risk of CVD. On multivariable analyses with conventional risk factors forced into the proportional hazards model, fibrinogen, D-dimer, and PAI-1 were significantly associated with risk of CVD, whereas factor VIIc showed an inverse association (P=0.001). In a model that contained the conventional risk factors, the hazard ratio for subsequent CVD in the top third of the distribution of predicted risk relative to the bottom third was 2.7 for subjects without preexisting CVD. This ratio increased to 3.7 for the model that also contained the 4 hemostatic factors. Fibrinogen, D-dimer, PAI-1 activity, and factor VIIc each has potential to increase the prediction of coronary disease/ischemic stroke in middle-aged men, in addition to conventional risk factors.
Sattar, Naveed; Welsh, Paul; Sarwar, Nadeem; Danesh, John; Di Angelantonio, Emanuele; Gudnason, Vilmundur; Davey Smith, George; Ebrahim, Shah; Lawlor, Debbie A
2010-03-01
Limited evidence suggests NT-proBNP improves prediction of coronary heart disease (CHD) events but further data are needed, especially in people without pre-existing CHD and in women. We measured NT-proBNP in serum from 162 women with incident CHD events and 1226 controls (60-79 years) in a case-control study nested within the prospective British Women's Heart and Health Study. All cases and controls were free from CHD at baseline. We related NT-proBNP to CHD event risk, and determined to what extent NT-proBNP enhanced CHD risk prediction beyond established risk factors. The odds ratio for CHD per 1 standard deviation increase in log(e)NT-proBNP was 1.37 (95% CI: 1.13-1.68) in analyses adjusted for established CHD risk factors, social class, CRP and insulin. However, addition of log(e)NT-proBNP did not improve the discrimination of a prediction model including age, social class, smoking, physical activity, lipids, fasting glucose, waist:hip ratio, hypertension, statin and aspirin use, nor a standard Framingham risk score model; area under the receiver operator curve for the former model increased from 0.676 to 0.687 on inclusion of NT-proBNP (p=0.3). Furthermore, adding NT-proBNP did not improve calibration of a prediction model containing established risk factors, nor did inclusion more appropriately re-classify participants in relation to their final outcome. Findings were similar (independent associations, but no prediction improvement) for fasting insulin and CRP. These results caution against use of NT-proBNP for CHD risk prediction in healthy women and suggest a need for larger studies in both genders to resolve outstanding uncertainties.
The Costs and Risks of Social Activism: A Study of Sanctuary Movement Activism.
ERIC Educational Resources Information Center
Wiltfang, Gregory L.; McAdam, Doug
1991-01-01
Among 141 activists with varying levels of participation in the sanctuary movement, biographical availability factors--younger age and greater discretionary time--best predict high-cost activism (more hours devoted to the movement), whereas ideological socialization factors best predict high-risk activism (direct contact with refugees). Contains…
Prati, Patrizio; Tosetto, Alberto; Vanuzzo, Diego; Bader, Giovanni; Casaroli, Marco; Canciani, Luigi; Castellani, Sergio; Touboul, Pierre-Jean
2008-09-01
The clinical usefulness of noninvasive measurement of carotid intima media thickness and plaque visualization in the general population is still uncertain. We evaluated the age-specific incidence rates of cerebrovascular events in a cohort of 1348 subjects randomly taken from the census list of San Daniele Township and followed for a mean period of 12.7 years. The association among common carotid intima media thickness, measured at baseline, arterial risk factors, and incidence of ischemic cerebrovascular events was modeled using Poisson regression. The predictive ability of common carotid intima media thickness over arterial risk factors (summarized in the Framingham Stroke Risk Score) was evaluated by receiver operating characteristic curve analysis. During the follow-up, 115 subjects developed nonfatal ischemic stroke, transient ischemic attack, or vascular death, which were the predefined study end points. After adjustment for age and sex, hypertension, diabetes, common carotid intima media thickness above 1 mm, and carotid plaques were all independent risk factors for development of vascular events. Inclusion of carotid findings (presence of common carotid intima media thickness above 1 mm or carotid plaques) resulted in a predictive power higher than Framingham Stroke Risk Score alone only on for those subjects with a Framingham Stroke Risk Score over 20%. Although common carotid intima media thickness and presence of carotid plaques are known to be risk factors for the development of vascular events and to be independent from the conventional risk factors summarized in the Framingham Stroke Risk Score, their contribution to individual risk prediction is limited. Further studies will be required to address the role of carotid ultrasonography in the primary prevention of high-risk subjects.
Mantovani, Alessandra M; Fregonesi, Cristina E P T; Palma, Mariana R; Ribeiro, Fernanda E; Fernandes, Rômulo A; Christofaro, Diego G D
Individuals with diabetes develop lower extremity amputation for several reasons. Investigations into pathways to the development of complications are important both for treatment and prevention. To evaluate the relationship between amputation and risk factors in people with diabetes mellitus. All participants included in this study (n=165) were recruited from the Diabetic Foot Program, developed in a Brazilian University, over seven years (2007-2014) and all information for this study was extracted from their clinical records. The prevalence of amputation in patients with diabetes with four risk factors was up to 20% higher when compared to those with only one risk factor. The main predictive risk factors for amputation in this population were the presence of an ulcer and smoking. The risk factors for amputation can be predicted for people with diabetes mellitus and, in the present study, the main factors were the presence of an ulcer and the smoking habit. Copyright © 2016 Diabetes India. Published by Elsevier Ltd. All rights reserved.
Assessing Suicide Risk Among Callers to Crisis Hotlines: A Confirmatory Factor Analysis
Witte, Tracy K.; Gould, Madelyn S.; Munfakh, Jimmie Lou Harris; Kleinman, Marjorie; Joiner, Thomas E.; Kalafat, John
2012-01-01
Our goal was to investigate the factor structure of a risk assessment tool utilized by suicide hotlines and to determine the predictive validity of the obtained factors in predicting subsequent suicidal behavior. 1,085 suicidal callers to crisis hotlines were divided into three sub-samples, which allowed us to conduct an independent Exploratory Factor Analysis (EFA), EFA in a Confirmatory Factor Analysis (EFA/CFA) framework, and CFA. Similar to previous factor analytic studies (Beck et al., 1997; Holden & DeLisle, 2005; Joiner, Rudd, & Rajab, 1997; Witte et al., 2006), we found consistent evidence for a two-factor solution, with one factor representing a more pernicious form of suicide risk (i.e., Resolved Plans and Preparations) and one factor representing more mild suicidal ideation (i.e., Suicidal Desire and Ideation). Using structural equation modeling techniques, we found preliminary evidence that the Resolved Plans and Preparations factor trended toward being more predictive of suicidal ideation than the Suicidal Desire and Ideation factor. This factor analytic study is the first longitudinal study of the obtained factors. PMID:20578186
Predictors of smoking lapse in a human laboratory paradigm.
Roche, Daniel J O; Bujarski, Spencer; Moallem, Nathasha R; Guzman, Iris; Shapiro, Jenessa R; Ray, Lara A
2014-07-01
During a smoking quit attempt, a single smoking lapse is highly predictive of future relapse. While several risk factors for a smoking lapse have been identified during clinical trials, a laboratory model of lapse was until recently unavailable and, therefore, it is unclear whether these characteristics also convey risk for lapse in a laboratory environment. The primary study goal was to examine whether real-world risk factors of lapse are also predictive of smoking behavior in a laboratory model of smoking lapse. After overnight abstinence, 77 smokers completed the McKee smoking lapse task, in which they were presented with the choice of smoking or delaying in exchange for monetary reinforcement. Primary outcome measures were the latency to initiate smoking behavior and the number of cigarettes smoked during the lapse. Several baseline measures of smoking behavior, mood, and individual traits were examined as predictive factors. Craving to relieve the discomfort of withdrawal, withdrawal severity, and tension level were negatively predictive of latency to smoke. In contrast, average number of cigarettes smoked per day, withdrawal severity, level of nicotine dependence, craving for the positive effects of smoking, and craving to relieve the discomfort of withdrawal were positively predictive of number of cigarettes smoked. The results suggest that real-world risk factors for smoking lapse are also predictive of smoking behavior in a laboratory model of lapse. Future studies using the McKee lapse task should account for between subject differences in the unique factors that independently predict each outcome measure.
Validation of Predictors of Fall Events in Hospitalized Patients With Cancer.
Weed-Pfaff, Samantha H; Nutter, Benjamin; Bena, James F; Forney, Jennifer; Field, Rosemary; Szoka, Lynn; Karius, Diana; Akins, Patti; Colvin, Christina M; Albert, Nancy M
2016-10-01
A seven-item cancer-specific fall risk tool (Cleveland Clinic Capone-Albert [CC-CA] Fall Risk Score) was shown to have a strong concordance index for predicting falls; however, validation of the model is needed. The aims of this study were to validate that the CC-CA Fall Risk Score, made up of six factors, predicts falls in patients with cancer and to determine if the CC-CA Fall Risk Score performs better than the Morse Fall Tool. Using a prospective, comparative methodology, data were collected from electronic health records of patients hospitalized for cancer care in four hospitals. Risk factors from each tool were recorded, when applicable. Multivariable models were created to predict the probability of a fall. A concordance index for each fall tool was calculated. The CC-CA Fall Risk Score provided higher discrimination than the Morse Fall Tool in predicting fall events in patients hospitalized for cancer management.
Gim, Jungsoo; Kim, Wonji; Kwak, Soo Heon; Choi, Hosik; Park, Changyi; Park, Kyong Soo; Kwon, Sunghoon; Park, Taesung; Won, Sungho
2017-11-01
Despite the many successes of genome-wide association studies (GWAS), the known susceptibility variants identified by GWAS have modest effect sizes, leading to notable skepticism about the effectiveness of building a risk prediction model from large-scale genetic data. However, in contrast to genetic variants, the family history of diseases has been largely accepted as an important risk factor in clinical diagnosis and risk prediction. Nevertheless, the complicated structures of the family history of diseases have limited their application in clinical practice. Here, we developed a new method that enables incorporation of the general family history of diseases with a liability threshold model, and propose a new analysis strategy for risk prediction with penalized regression analysis that incorporates both large numbers of genetic variants and clinical risk factors. Application of our model to type 2 diabetes in the Korean population (1846 cases and 1846 controls) demonstrated that single-nucleotide polymorphisms accounted for 32.5% of the variation explained by the predicted risk scores in the test data set, and incorporation of family history led to an additional 6.3% improvement in prediction. Our results illustrate that family medical history provides valuable information on the variation of complex diseases and improves prediction performance. Copyright © 2017 by the Genetics Society of America.
Murray, Joseph; Maughan, Barbara; Menezes, Ana M B; Hickman, Matthew; MacLeod, John; Matijasevich, Alicia; Gonçalves, Helen; Anselmi, Luciana; Gallo, Erika A G; Barros, Fernando C
2015-08-01
Many low- and middle-income countries have high levels of violence. Research in high-income countries shows that risk factors in the perinatal period are significant precursors of conduct problems which can develop into violence. It is not known whether the same early influences are important in lower income settings with higher rates of violence. This study compared perinatal and sociodemographic risk factors between Brazil and Britain, and their role in explaining higher rates of conduct problems and violence in Brazil. Prospective population-based birth cohort studies were conducted in Pelotas, Brazil (N = 3,618) and Avon, Britain (N = 4,103). Eleven perinatal and sociodemographic risk factors were measured in questionnaires completed by mothers during the perinatal period. Conduct problems were measured in questionnaires completed by mothers at age 11, and violence in self-report questionnaires completed by adolescents at age 18. Conduct problems were predicted by similar risk factors in Brazil and Britain. Female violence was predicted by several of the same risk factors in both countries. However, male violence in Brazil was associated with only one risk factor, and several risk factor associations were weaker in Brazil than in Britain for both females and males. Almost 20% of the higher risk for conduct problems in Brazil compared to Britain was explained by differential exposure to risk factors. The percentage of the cross-national difference in violence explained by early risk factors was 15% for females and 8% for males. A nontrivial proportion of cross-national differences in antisocial behaviour are related to perinatal and sociodemographic conditions at the start of life. However, risk factor associations are weaker in Brazil than in Britain, and influences in other developmental periods are probably of particular importance for understanding male youth violence in Brazil. © 2014 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.
Bohn, Barbara; Müller, Manfred James; Simic-Schleicher, Gunter; Kiess, Wieland; Siegfried, Wolfgang; Oelert, Monika; Tuschy, Sabine; Berghem, Stefan; Holl, Reinhard W
2015-01-01
Body fat (BF) percentiles for German children and adolescents have recently been published. This study aims to evaluate the association between bioelectrical impedance analysis (BIA)-derived BF and cardiovascular risk factors and to investigate whether BF is better suited than BMI in children and adolescents. Data of 3,327 children and adolescents (BMI > 90th percentile) were included. Spearman's correlation and receiver operating characteristics (ROCs) were applied determining the associations between BMI or BF and cardiovascular risk factors (hypertension, dyslipidemia, elevated liver enzymes, abnormal carbohydrate metabolism). Area under the curve (AUC) was calculated to predict cardiovascular risk factors. A significant association between both obesity indices and hypertension was present (all p < 0.0001), but the correlation with BMI was stronger (r = 0.22) compared to BF (r = 0.13). There were no differences between BMI and BF regarding their correlation with other cardiovascular risk factors. BF significantly predicted hypertension (AUC = 0.61), decreased HDL-cholesterol (AUC = 0.58), elevated LDL-cholesterol (AUC = 0.59), elevated liver enzymes (AUC = 0.61) (all p < 0.0001), and elevated triglycerides (AUC = 0.57, p < 0.05), but not abnormal carbohydrate metabolism (AUC = 0.54, p = 0.15). For the prediction of cardiovascular risk factors, no significant differences between BMI and BF were observed. BIA-derived BF was not superior to BMI to predict cardiovascular risk factors in overweight or obese children and adolescents.
Batterham, Philip J; Christensen, Helen; Mackinnon, Andrew J
2009-11-22
Relative to physical health conditions such as cardiovascular disease, little is known about risk factors that predict the prevalence of depression. The present study investigates the expected effects of a reduction of these risks over time, using the decision tree method favoured in assessing cardiovascular disease risk. The PATH through Life cohort was used for the study, comprising 2,105 20-24 year olds, 2,323 40-44 year olds and 2,177 60-64 year olds sampled from the community in the Canberra region, Australia. A decision tree methodology was used to predict the presence of major depressive disorder after four years of follow-up. The decision tree was compared with a logistic regression analysis using ROC curves. The decision tree was found to distinguish and delineate a wide range of risk profiles. Previous depressive symptoms were most highly predictive of depression after four years, however, modifiable risk factors such as substance use and employment status played significant roles in assessing the risk of depression. The decision tree was found to have better sensitivity and specificity than a logistic regression using identical predictors. The decision tree method was useful in assessing the risk of major depressive disorder over four years. Application of the model to the development of a predictive tool for tailored interventions is discussed.
Chao, Tze-Fan; Lip, Gregory Y H; Lin, Yenn-Jiang; Chang, Shih-Lin; Lo, Li-Wei; Hu, Yu-Feng; Tuan, Ta-Chuan; Liao, Jo-Nan; Chung, Fa-Po; Chen, Tzeng-Ji; Chen, Shih-Ann
2018-04-01
When assessing bleeding risk in patients with atrial fibrillation (AF), risk stratification is often based on the baseline risks. We aimed to investigate changes in bleeding risk factors and alterations in the HAS-BLED score in AF patients. We hypothesized that a follow-up HAS-BLED score and the 'delta HAS-BLED score' (reflecting the change in score between baseline and follow-up) would be more predictive of major bleeding, when compared with baseline HAS-BLED score. A total of 19,566 AF patients receiving warfarin and baseline HAS-BLED score ≤2 were studied. After a follow-up of 93,783 person-years, 3,032 major bleeds were observed. The accuracies of baseline, follow-up, and delta HAS-BLED scores as well as cumulative numbers of baseline modifiable bleeding risk factors, in predicting subsequent major bleeding, were analysed and compared. The mean baseline HAS-BLED score was 1.43 which increased to 2.45 with a mean 'delta HAS-BLED score' of 1.03. The HAS-BLED score remained unchanged in 38.2% of patients. Of those patients experiencing major bleeding, 76.6% had a 'delta HAS-BLED' score ≥1, compared with only 59.0% in patients without major bleeding ( p < 0.001). For prediction of major bleeding, AUC was significantly higher for the follow-up HAS-BLED (0.63) or delta HAS-BLED (0.62) scores, compared with baseline HAS-BLED score (0.54). The number of baseline modifiable risk factors was non-significantly predictive of major bleeding (AUC = 0.49). In this 'real-world' nationwide AF cohort, follow-up HAS-BLED or 'delta HAS-BLED score' was more predictive of major bleeding compared with baseline HAS-BLED or the simple determination of 'modifiable bleeding risk factors'. Bleeding risk in AF is a dynamic process and use of the HAS-BLED score should be to 'flag up' patients potentially at risk for more regular review and follow-up, and to address the modifiable bleeding risk factors during follow-up visits. Schattauer GmbH Stuttgart.
Shechory Bitton, Mally; Ben-David, Sarah
2014-12-01
The current study of 668 Israeli male and female students examines the prevalence of gendered risk factors for sexual assault (SA) on dates, posttraumatic stress disorder (PTSD) as a detrimental effect of SA, and self-efficacy as resiliency to refuse unwanted sex following SA. Two different sets of risk factors that increased the likelihood of SA on dates emerged from the hierarchical regression. Sexual experience, use of drugs, and private location increased the risk of being SA victims among males, whereas sexual experience, perceived provocative behavior, and alcohol use increased the risk among females. In addition, PTSD and self-efficacy to refuse unwanted sex following SA on dates were predicted by the extent of coercive sexual victimization. PTSD was also predicted by subjective perception of sexual behavior and rape myths, whereas efficacy was predicted by private location. The findings contribute to the literature by showing the contribution of various risk factors to experiencing SA, and by showing SA effect on PTSD and self-efficacy. © The Author(s) 2013.
Prediction of concurrent endometrial carcinoma in women with endometrial hyperplasia.
Matsuo, Koji; Ramzan, Amin A; Gualtieri, Marc R; Mhawech-Fauceglia, Paulette; Machida, Hiroko; Moeini, Aida; Dancz, Christina E; Ueda, Yutaka; Roman, Lynda D
2015-11-01
Although a fraction of endometrial hyperplasia cases have concurrent endometrial carcinoma, patient characteristics associated with concurrent malignancy are not well described. The aim of our study was to identify predictive clinico-pathologic factors for concurrent endometrial carcinoma among patients with endometrial hyperplasia. A case-control study was conducted to compare endometrial hyperplasia in both preoperative endometrial biopsy and hysterectomy specimens (n=168) and endometrial carcinoma in hysterectomy specimen but endometrial hyperplasia in preoperative endometrial biopsy (n=43). Clinico-pathologic factors were examined to identify independent risk factors of concurrent endometrial carcinoma in a multivariate logistic regression model. The most common histologic subtype in preoperative endometrial biopsy was complex hyperplasia with atypia [CAH] (n=129) followed by complex hyperplasia without atypia (n=58) and simple hyperplasia with or without atypia (n=24). The majority of endometrial carcinomas were grade 1 (86.0%) and stage I (83.7%). In multivariate analysis, age 40-59 (odds ratio [OR] 3.07, p=0.021), age≥60 (OR 6.65, p=0.005), BMI≥35kg/m(2) (OR 2.32, p=0.029), diabetes mellitus (OR 2.51, p=0.019), and CAH (OR 9.01, p=0.042) were independent predictors of concurrent endometrial carcinoma. The risk of concurrent endometrial carcinoma rose dramatically with increasing number of risk factors identified in multivariate model (none 0%, 1 risk factor 7.0%, 2 risk factors 17.6%, 3 risk factors 35.8%, and 4 risk factors 45.5%, p<0.001). Hormonal treatment was associated with decreased risk of concurrent endometrial cancer in those with ≥3 risk factors. Older age, obesity, diabetes mellitus, and CAH are predictive of concurrent endometrial carcinoma in endometrial hyperplasia patients. Copyright © 2015 Elsevier Inc. All rights reserved.
Clinical Utility of Five Genetic Variants for Predicting Prostate Cancer Risk and Mortality
Salinas, Claudia A.; Koopmeiners, Joseph S.; Kwon, Erika M.; FitzGerald, Liesel; Lin, Daniel W.; Ostrander, Elaine A.; Feng, Ziding; Stanford, Janet L.
2009-01-01
Background A recent report suggests that the combination of five single-nucleotide polymorphisms (SNPs) at 8q24, 17q12, 17q24.3 and a family history of the disease may predict risk of prostate cancer. The present study tests the performance of these factors in prediction models for prostate cancer risk and prostate cancer-specific mortality. Methods SNPs were genotyped in population-based samples from Caucasians in King County, Washington. Incident cases (n=1308), aged 35–74, were compared to age-matched controls (n=1266) using logistic regression to estimate odds ratios (OR) associated with genotypes and family history. Cox proportional hazards models estimated hazard ratios for prostate cancer-specific mortality according to genotypes. Results The combination of SNP genotypes and family history was significantly associated with prostate cancer risk (ptrend=1.5 × 10−20). Men with ≥ five risk factors had an OR of 4.9 (95% CI 1.6 to 18.5) compared to men with none. However, this combination of factors did not improve the ROC curve after accounting for known risk predictors (i.e., age, serum PSA, family history). Neither the individual nor combined risk factors was associated with prostate cancer-specific mortality. Conclusion Genotypes for five SNPs plus family history are associated with a significant elevation in risk for prostate cancer and may explain up to 45% of prostate cancer in our population. However, they do not improve prediction models for assessing who is at risk of getting or dying from the disease, once known risk or prognostic factors are taken into account. Thus, this SNP panel may have limited clinical utility. PMID:19058137
Davis, Cynthia R.; Dearing, Eric; Usher, Nicole; Trifiletti, Sarah; Zaichenko, Lesya; Ollen, Elizabeth; Brinkoetter, Mary T.; Crowell-Doom, Cindy; Joung, Kyoung; Park, Kyung Hee; Mantzoros, Christos S.; Crowell, Judith A.
2017-01-01
Objective This study examined whether a novel indicator of overall childhood adversity, incorporating number of adversities, severity, and chronicity, predicted central obesity beyond contributions of “modifiable” risk factors including psychosocial characteristics and health behaviors in a diverse sample of midlife adults. The study also examined whether the overall adversity score (number of adversities X severity X chronicity) better predicted obesity compared to cumulative adversity (number of adversities), a more traditional assessment of childhood adversity. Materials/Methods 210 Black/African Americans and White/European Americans, mean age = 45.8; ±3.3 years, were studied cross-sectionally. Regression analysis examined overall childhood adversity as a direct, non-modifiable risk factor for central obesity (waist-hip ratio) and body mass index (BMI), with and without adjustment for established adult psychosocial risk factors (education, employment, social functioning) and heath behavior risk factors (smoking, drinking, diet, exercise). Results Overall childhood adversity was an independent significant predictor of central obesity, and the relations between psychosocial and health risk factors and central obesity were not significant when overall adversity was in the model. Overall adversity was not a statistically significant predictor of BMI. Conclusions Overall childhood adversity, incorporating severity and chronicity and cumulative scores, predicts central obesity beyond more contemporaneous risk factors often considered modifiable. This is consistent with early dysregulation of metabolic functioning. Findings can inform practitioners interested in the impact of childhood adversity and personalizing treatment approaches of obesity within high-risk populations. Prevention/intervention research is necessary to discover and address the underlying causes and impact of childhood adversity on metabolic functioning. PMID:24211017
Alvarez, Karina; Loehr, Laura; Folsom, Aaron R.; Newman, Anne B.; Weissfeld, Lisa A.; Wunderink, Richard G.; Kritchevsky, Stephen B.; Mukamal, Kenneth J.; London, Stephanie J.; Harris, Tamara B.; Bauer, Doug C.; Angus, Derek C.
2013-01-01
Background: Preventing pneumonia requires better understanding of incidence, mortality, and long-term clinical and biologic risk factors, particularly in younger individuals. Methods: This was a cohort study in three population-based cohorts of community-dwelling individuals. A derivation cohort (n = 16,260) was used to determine incidence and survival and develop a risk prediction model. The prediction model was validated in two cohorts (n = 8,495). The primary outcome was 10-year risk of pneumonia hospitalization. Results: The crude and age-adjusted incidences of pneumonia were 6.71 and 9.43 cases/1,000 person-years (10-year risk was 6.15%). The 30-day and 1-year mortality were 16.5% and 31.5%. Although age was the most important risk factor (range of crude incidence rates, 1.69-39.13 cases/1,000 person-years for each 5-year increment from 45-85 years), 38% of pneumonia cases occurred in adults < 65 years of age. The 30-day and 1-year mortality were 12.5% and 25.7% in those < 65 years of age. Although most comorbidities were associated with higher risk of pneumonia, reduced lung function was the most important risk factor (relative risk = 6.61 for severe reduction based on FEV1 by spirometry). A clinical risk prediction model based on age, smoking, and lung function predicted 10-year risk (area under curve [AUC] = 0.77 and Hosmer-Lemeshow [HL] C statistic = 0.12). Model discrimination and calibration were similar in the internal validation cohort (AUC = 0.77; HL C statistic, 0.65) but lower in the external validation cohort (AUC = 0.62; HL C statistic, 0.45). The model also calibrated well in blacks and younger adults. C-reactive protein and IL-6 were associated with higher pneumonia risk but did not improve model performance. Conclusions: Pneumonia hospitalization is common and associated with high mortality, even in younger healthy adults. Long-term risk of pneumonia can be predicted in community-dwelling adults with a simple clinical risk prediction model. PMID:23744106
Aljohani, Naji; Al Serehi, Amal; Ahmed, Amjad M; Buhary, Badr Aldin M; Alzahrani, Saad; At-Taras, Eeman; Almujally, Najla; Alsharqi, Maha; Alqahtani, Mohammed; Almalki, Mussa
2015-01-01
There is scarcity of available information on the possible significant risk factors related to diabetes mellitus (DM) prediction among expectant Saudi mothers with gestational diabetes mellitus (GDM). The present study is the first to identify such risk factors in the Arab cohort. A total of 300 pregnant subjects (mean age 33.45 ± 6.5 years) were randomly selected from all the deliveries registered at the Obstetrics Department of King Fahad Medical City, Riyadh Saudi Arabia from April 2011 to March 2013. Demographic and baseline glycemic information were collected. A total of 7 highly significant and independent risk factors were identified: age, obesity, and family history of DM, GDM < 20 weeks, macrosomia, insulin therapy and recurrent GDM. Among these factors, subjects who had insulin therapy use are 5 times more likely to develop DMT2 (p-value 3.94 × 10(-14)) followed by recurrent GDM [odds-ratio 4.69 (Confidence Interval 2.34-4.84); P = 1.24 × 10(-13)). The identification of the risk factors mentioned with their respective predictive powers in the detection of DMT2 needs to be taken seriously in the post-partum assessment of Saudi pregnant patients at highest risk.
Salazar-Fraile, José; Ripoll-Alandes, Carmen; Bobes, Julio
2010-01-01
Although a high prevalence of personality disorders has been reported in substance users, the literature on their value for predicting treatment response is controversial. On the other hand, while the predictive validity of personality traits as predictors of response to drug abuse or dependence has been studied, research on the validity of narcissistic personality traits is scarce. To study the predictive value of personality disorders, narcissistic personality traits and self-esteem for predicting treatment response. We assessed 78 patients attended at an addiction treatment unit using personality disorder diagnoses and measures of self-esteem, narcissism and covert (hypersensitive) narcissism. These variables were used in a Cox survival model as predictive variables of time to relapse into drug use. Hypersensitive (covert) narcissism and borderline and passive-aggressive personality disorders were risk factors for relapse into drug use, while open narcissism was a protective factor. Self-esteem did not show predictive validity. Personality disorders characterized by impulsivity-instability and passivity-resentfulness show higher risk of relapse into drug abuse. Personality traits characterized by high sensitivity to humiliation increase the risk of relapse, whereas pride and self-confidence are protective factors.
Prediction of acute kidney injury within 30 days of cardiac surgery.
Ng, Shu Yi; Sanagou, Masoumeh; Wolfe, Rory; Cochrane, Andrew; Smith, Julian A; Reid, Christopher Michael
2014-06-01
To predict acute kidney injury after cardiac surgery. The study included 28,422 cardiac surgery patients who had had no preoperative renal dialysis from June 2001 to June 2009 in 18 hospitals. Logistic regression analyses were undertaken to identify the best combination of risk factors for predicting acute kidney injury. Two models were developed, one including the preoperative risk factors and another including the pre-, peri-, and early postoperative risk factors. The area under the receiver operating characteristic curve was calculated, using split-sample internal validation, to assess model discrimination. The incidence of acute kidney injury was 5.8% (1642 patients). The mortality for patients who experienced acute kidney injury was 17.4% versus 1.6% for patients who did not. On validation, the area under the curve for the preoperative model was 0.77, and the Hosmer-Lemeshow goodness-of-fit P value was .06. For the postoperative model area under the curve was 0.81 and the Hosmer-Lemeshow P value was .6. Both models had good discrimination and acceptable calibration. Acute kidney injury after cardiac surgery can be predicted using preoperative risk factors alone or, with greater accuracy, using pre-, peri-, and early postoperative risk factors. The ability to identify high-risk individuals can be useful in preoperative patient management and for recruitment of appropriate patients to clinical trials. Prediction in the early stages of postoperative care can guide subsequent intensive care of patients and could also be the basis of a retrospective performance audit tool. Copyright © 2014 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.
Chao, Chun; Song, Yiqing; Cook, Nancy; Tseng, Chi-Hong; Manson, JoAnn E.; Eaton, Charles; Margolis, Karen L.; Rodriguez, Beatriz; Phillips, Lawrence S.; Tinker, Lesley F.; Liu, Simin
2011-01-01
Background Recent studies have linked plasma markers of inflammation and endothelial dysfunction to type 2 diabetes mellitus (DM) development. However, the utility of these novel biomarkers for type 2 DM risk prediction remains uncertain. Methods The Women’s Health Initiative Observational Study (WHIOS), a prospective cohort, and a nested case-control study within the WHIOS of 1584 incident type 2 DM cases and 2198 matched controls were used to evaluate the utility of plasma markers of inflammation and endothelial dysfunction for type 2 DM risk prediction. Between September 1994 and December 1998, 93 676 women aged 50 to 79 years were enrolled in the WHIOS. Fasting plasma levels of glucose, insulin, white blood cells, tumor necrosis factor receptor 2, interleukin 6, high-sensitivity C-reactive protein, E-selectin, soluble intercellular adhesion molecule 1, and vascular cell adhesion molecule 1 were measured using blood samples collected at baseline. A series of prediction models including traditional risk factors and novel plasma markers were evaluated on the basis of global model fit, model discrimination, net reclassification improvement, and positive and negative predictive values. Results Although white blood cell count and levels of interleukin 6, high-sensitivity C-reactive protein, and soluble intercellular adhesion molecule 1 significantly enhanced model fit, none of the inflammatory and endothelial dysfunction markers improved the ability of model discrimination (area under the receiver operating characteristic curve, 0.93 vs 0.93), net reclassification, or predictive values (positive, 0.22 vs 0.24; negative, 0.99 vs 0.99 [using 15% 6-year type 2 DM risk as the cutoff]) compared with traditional risk factors. Similar results were obtained in ethnic-specific analyses. Conclusion Beyond traditional risk factors, measurement of plasma markers of systemic inflammation and endothelial dysfunction contribute relatively little additional value in clinical type 2 DM risk prediction in a multiethnic cohort of postmenopausal women. PMID:20876407
High EDSS can predict risk for upper urinary tract damage in patients with multiple sclerosis.
Ineichen, Benjamin V; Schneider, Marc P; Hlavica, Martin; Hagenbuch, Niels; Linnebank, Michael; Kessler, Thomas M
2018-04-01
Neurogenic lower urinary tract dysfunction (NLUTD) is very common in patients with multiple sclerosis (MS), and it might jeopardize renal function and thereby increase mortality. Although there are well-known urodynamic risk factors for upper urinary tract damage, no clinical prediction parameters are available. We aimed to assess clinical parameters potentially predicting urodynamic risk factors for upper urinary tract damage. A consecutive series of 141 patients with MS referred from neurologists for primary neuro-urological work-up including urodynamics were prospectively evaluated. Clinical parameters taken into account were age, sex, duration, and clinical course of MS and Expanded Disability Status Scale (EDSS). Multivariate modeling revealed EDSS as a clinical parameter significantly associated with urodynamic risk factors for upper urinary tract damage (odds ratio = 1.34, 95% confidence interval (CI) = 1.06-1.71, p = 0.02). Using receiver operator characteristic (ROC) curves, an EDSS of 5.0 as cutoff showed a sensitivity of 86%-87% and a specificity of 52% for at least one urodynamic risk factor for upper urinary tract damage. High EDSS is significantly associated with urodynamic risk factors for upper urinary tract damage and allows a risk-dependent stratification in daily neurological clinical practice to identify MS patients requiring further neuro-urological assessment and treatment.
Guan, Ling; Collet, Jean-Paul; Mazowita, Garey; Claydon, Victoria E
2018-01-01
Transient ischemic attack (TIA) and minor stroke have high risks of recurrence and deterioration into severe ischemic strokes. Risk stratification of TIA and minor stroke is essential for early effective treatment. Traditional tools have only moderate predictive value, likely due to their inclusion of the limited number of stroke risk factors. Our review follows Hans Selye's fundamental work on stress theory and the progressive shift of the autonomic nervous system (ANS) from adaptation to disease when stress becomes chronic. We will first show that traditional risk factors and acute triggers of ischemic stroke are chronic and acute stress factors or "stressors," respectively. Our first review shows solid evidence of the relationship between chronic stress and stroke occurrence. The stress response is tightly regulated by the ANS whose function can be assessed with heart rate variability (HRV). Our second review demonstrates that stress-related risk factors of ischemic stroke are correlated with ANS dysfunction and impaired HRV. Our conclusions support the idea that HRV parameters may represent the combined effects of all body stressors that are risk factors for ischemic stroke and, thus, may be of important predictive value for the risk of subsequent ischemic events after TIA or minor stroke.
Guan, Ling; Collet, Jean-Paul; Mazowita, Garey; Claydon, Victoria E.
2018-01-01
Transient ischemic attack (TIA) and minor stroke have high risks of recurrence and deterioration into severe ischemic strokes. Risk stratification of TIA and minor stroke is essential for early effective treatment. Traditional tools have only moderate predictive value, likely due to their inclusion of the limited number of stroke risk factors. Our review follows Hans Selye’s fundamental work on stress theory and the progressive shift of the autonomic nervous system (ANS) from adaptation to disease when stress becomes chronic. We will first show that traditional risk factors and acute triggers of ischemic stroke are chronic and acute stress factors or “stressors,” respectively. Our first review shows solid evidence of the relationship between chronic stress and stroke occurrence. The stress response is tightly regulated by the ANS whose function can be assessed with heart rate variability (HRV). Our second review demonstrates that stress-related risk factors of ischemic stroke are correlated with ANS dysfunction and impaired HRV. Our conclusions support the idea that HRV parameters may represent the combined effects of all body stressors that are risk factors for ischemic stroke and, thus, may be of important predictive value for the risk of subsequent ischemic events after TIA or minor stroke. PMID:29556209
Choi, Soo Beom; Lee, Wanhyung; Yoon, Jin-Ha; Won, Jong-Uk; Kim, Deok Won
2017-06-15
Suicide is a serious public health concern worldwide, and the fourth leading cause of death in Korea. Few studies have focused on risk factors for suicide attempt among people with suicidal ideation. The aim of the present study was to investigate the risk factors and develop prediction models for suicide attempt among people with suicidal ideation in the Korean population. This study included 1567 men and 3726 women aged 20 years and older who had suicidal ideation from the Korea National Health and Nutrition Examination Survey from 2007 to 2012. Among them, 106 men and 188 women attempted suicide. Multivariate logistic regression analysis with backward stepwise elimination was performed to find risk factors for suicide attempt. Sub-group analysis, dividing participants into under 50 and at least 50 years old was also performed. Among people with suicidal ideation, age, education, cancer, and depressive disorder were selected as risk factors for suicide attempt in men. Age, education, national basic livelihood security, daily activity limitation, depressive disorder, stress, smoking, and regular exercise were selected in women. Area under curves of our prediction models in men and women were 0.728 and 0.716, respectively. It is important to pay attention to populations with suicidal ideation and the risk factors mentioned above. Prediction models using the determined risk factors could be useful to detect high-risk groups early for suicide attempt among people with suicidal ideation. It is necessary to develop specific action plans for these high-risk groups to prevent suicide.
Glycated hemoglobin measurement and prediction of cardiovascular disease.
Di Angelantonio, Emanuele; Gao, Pei; Khan, Hassan; Butterworth, Adam S; Wormser, David; Kaptoge, Stephen; Kondapally Seshasai, Sreenivasa Rao; Thompson, Alex; Sarwar, Nadeem; Willeit, Peter; Ridker, Paul M; Barr, Elizabeth L M; Khaw, Kay-Tee; Psaty, Bruce M; Brenner, Hermann; Balkau, Beverley; Dekker, Jacqueline M; Lawlor, Debbie A; Daimon, Makoto; Willeit, Johann; Njølstad, Inger; Nissinen, Aulikki; Brunner, Eric J; Kuller, Lewis H; Price, Jackie F; Sundström, Johan; Knuiman, Matthew W; Feskens, Edith J M; Verschuren, W M M; Wald, Nicholas; Bakker, Stephan J L; Whincup, Peter H; Ford, Ian; Goldbourt, Uri; Gómez-de-la-Cámara, Agustín; Gallacher, John; Simons, Leon A; Rosengren, Annika; Sutherland, Susan E; Björkelund, Cecilia; Blazer, Dan G; Wassertheil-Smoller, Sylvia; Onat, Altan; Marín Ibañez, Alejandro; Casiglia, Edoardo; Jukema, J Wouter; Simpson, Lara M; Giampaoli, Simona; Nordestgaard, Børge G; Selmer, Randi; Wennberg, Patrik; Kauhanen, Jussi; Salonen, Jukka T; Dankner, Rachel; Barrett-Connor, Elizabeth; Kavousi, Maryam; Gudnason, Vilmundur; Evans, Denis; Wallace, Robert B; Cushman, Mary; D'Agostino, Ralph B; Umans, Jason G; Kiyohara, Yutaka; Nakagawa, Hidaeki; Sato, Shinichi; Gillum, Richard F; Folsom, Aaron R; van der Schouw, Yvonne T; Moons, Karel G; Griffin, Simon J; Sattar, Naveed; Wareham, Nicholas J; Selvin, Elizabeth; Thompson, Simon G; Danesh, John
2014-03-26
The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. Analysis of individual-participant data available from 73 prospective studies involving 294,998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥ 7.5%) risk. During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20,840 incident fatal and nonfatal CVD outcomes (13,237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.
Teachers' Knowledge of Children's Exposure to Family Risk Factors: Accuracy and Usefulness
ERIC Educational Resources Information Center
Dwyer, Sarah B.; Nicholson, Jan M.; Battistutta, Diana; Oldenburg, Brian
2005-01-01
Teachers' knowledge of children's exposure to family risk factors was examined using the Family Risk Factor Checklist-Teacher. Data collected for 756 children indicated that teachers had accurate knowledge of children's exposure to factors such as adverse life events and family socioeconomic status, which predicted children's mental health…
Identifying Causal Risk Factors for Violence among Discharged Patients
Coid, Jeremy W.; Kallis, Constantinos; Doyle, Mike; Shaw, Jenny; Ullrich, Simone
2015-01-01
Background Structured Professional Judgement (SPJ) is routinely administered in mental health and criminal justice settings but cannot identify violence risk above moderate accuracy. There is no current evidence that violence can be prevented using SPJ. This may be explained by routine application of predictive instead of causal statistical models when standardising SPJ instruments. Methods We carried out a prospective cohort study of 409 male and female patients discharged from medium secure services in England and Wales to the community. Measures were taken at baseline (pre-discharge), 6 and 12 months post-discharge using the Historical, Clinical and Risk-20 items version 3 (HCR-20v3) and Structural Assessment of Protective Factors (SAPROF). Information on violence was obtained via the McArthur community violence instrument and the Police National Computer. Results In a lagged model, HCR-20v3 and SAPROF items were poor predictors of violence. Eight items of the HCR-20v3 and 4 SAPROF items did not predict violent behaviour better than chance. In re-analyses considering temporal proximity of risk/ protective factors (exposure) on violence (outcome), risk was elevated due to violent ideation (OR 6.98, 95% CI 13.85–12.65, P<0.001), instability (OR 5.41, 95% CI 3.44–8.50, P<0.001), and poor coping/ stress (OR 8.35, 95% CI 4.21–16.57, P<0.001). All 3 risk factors were explanatory variables which drove the association with violent outcome. Self-control (OR 0.13, 95% CI 0.08–0.24, P<0.001) conveyed protective effects and explained the association of other protective factors with violence. Conclusions Using two standardised SPJ instruments, predictive (lagged) methods could not identify risk and protective factors which must be targeted in interventions for discharged patients with severe mental illness. Predictive methods should be abandoned if the aim is to progress from risk assessment to effective risk management and replaced by methods which identify factors causally associated with violence. PMID:26554711
Dorsey, Karen B; Mauldon, Maria; Magraw, Ruth; Yu, Sunkyung; Krumholz, Harlan M
2010-10-01
To determine whether information gathered during routine healthcare visits regarding obesity related risk factors and risk behaviors predicts increases in BMI z-score over time among overweight and obese children. Medical records from 168 overweight and 441 obese patients seen for repeated visits between September 2003 and April 2006 were examined for reported dietary, physical activity, and sedentary behaviors, family history of obesity and diabetes mellitus, documented Acanthosis nigricans, and BMI values. Random-effects regression analysis was done to determine whether demographic, familial, or behavioral data predicted changes in BMI z-score over time. The presence of A nigricans and a family history of obesity were associated with an increase in BMI z-score (beta=0.56, SE=0.09, P<.001 and beta=0.31, SE=0.13, P=.021). These risk factors explained 8% and 7% of the variation in BMI z-score respectively. Self- or parent-reported dietary and physical activity behaviors did not predict change in BMI z-score. Our findings suggest that the risk factors and self- or parent-reported risk behaviors routinely assessed by pediatric clinicians have limited ability to predict future growth trends, demonstrating the difficulty in determining which patients have the greatest risk of progression of obesity. Copyright (c) 2010 Mosby, Inc. All rights reserved.
Fried, Eiko I.; Nesse, Randolph M.; Zivin, Kara; Guille, Constance; Sen, Srijan
2014-01-01
Background For diagnostic purposes, the nine symptoms that compose the DSM-5 criteria for Major Depressive Disorder (MDD) are assumed to be interchangeable indicators of one underlying disorder, implying that they should all have similar risk factors. The present study investigates this hypothesis, utilizing a population cohort that shifts from low to elevated depression levels. Methods We assessed the nine DSM-5 MDD criterion symptoms and seven depression risk factors (personal and family MDD history, sex, childhood stress, neuroticism, work hours, and stressful life events) in a longitudinal study of medical interns prior to and throughout internship (n=1289). We tested if risk factors varied across symptoms, and whether a latent disease model could account for heterogeneity between symptoms. Results All MDD symptoms increased significantly during residency training. Four risk factors predicted increases in unique subsets of PHQ-9 symptoms over time (depression history, childhood stress, sex, and stressful life events), while neuroticism and work hours predicted increases in all symptoms, albeit to varying magnitudes. MDD family history did not predict increases in any symptom. The strong heterogeneity of associations persisted after controlling for a latent depression factor. Conclusions The influence of risk factors varies substantially across DSM depression criterion symptoms. Since symptoms are etiologically heterogeneous, considering individual symptoms in addition to depression diagnosis might offer important insights obfuscated by symptom sum-scores. PMID:24289852
Dilnot, Julia; Hamilton, Lorna; Maughan, Barbara; Snowling, Margaret J
2017-02-01
We investigate the role of distal, proximal, and child risk factors as predictors of reading readiness and attention and behavior in children at risk of dyslexia. The parents of a longitudinal sample of 251 preschool children, including children at family risk of dyslexia and children with preschool language difficulties, provided measures of socioeconomic status, home literacy environment, family stresses, and child health via interviews and questionnaires. Assessments of children's reading-related skills, behavior, and attention were used to define their readiness for learning at school entry. Children at family risk of dyslexia and children with preschool language difficulties experienced more environmental adversities and health risks than controls. The risks associated with family risk of dyslexia and with language status were additive. Both home literacy environment and child health predicted reading readiness while home literacy environment and family stresses predicted attention and behavior. Family risk of dyslexia did not predict readiness to learn once other risks were controlled and so seems likely to be best conceptualized as representing gene-environment correlations. Pooling across risks defined a cumulative risk index, which was a significant predictor of reading readiness and, together with nonverbal ability, accounted for 31% of the variance between children.
Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.
Ibrahim-Verbaas, Carla A; Fornage, Myriam; Bis, Joshua C; Choi, Seung Hoan; Psaty, Bruce M; Meigs, James B; Rao, Madhu; Nalls, Mike; Fontes, Joao D; O'Donnell, Christopher J; Kathiresan, Sekar; Ehret, Georg B; Fox, Caroline S; Malik, Rainer; Dichgans, Martin; Schmidt, Helena; Lahti, Jari; Heckbert, Susan R; Lumley, Thomas; Rice, Kenneth; Rotter, Jerome I; Taylor, Kent D; Folsom, Aaron R; Boerwinkle, Eric; Rosamond, Wayne D; Shahar, Eyal; Gottesman, Rebecca F; Koudstaal, Peter J; Amin, Najaf; Wieberdink, Renske G; Dehghan, Abbas; Hofman, Albert; Uitterlinden, André G; Destefano, Anita L; Debette, Stephanie; Xue, Luting; Beiser, Alexa; Wolf, Philip A; Decarli, Charles; Ikram, M Arfan; Seshadri, Sudha; Mosley, Thomas H; Longstreth, W T; van Duijn, Cornelia M; Launer, Lenore J
2014-02-01
Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors. The study includes 4 population-based cohorts with 2047 first incident strokes from 22,720 initially stroke-free European origin participants aged ≥55 years, who were followed for up to 20 years. GRSs were constructed with 324 single-nucleotide polymorphisms implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with area under the curve statistics comparing the GRS with age and sex, Framingham Stroke Risk Score models, and reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke. In the meta-analysis, adding the GRS to the Framingham Stroke Risk Score, age and sex model resulted in a significant improvement in discrimination (all stroke: Δjoint area under the curve=0.016, P=2.3×10(-6); ischemic stroke: Δjoint area under the curve=0.021, P=3.7×10(-7)), although the overall area under the curve remained low. In all the studies, there was a highly significantly improved net reclassification index (P<10(-4)). The single-nucleotide polymorphisms associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared with the classical epidemiological risk factors for stroke.
Wojciechowski, Thomas W
2017-10-01
Past research has identified attention-deficit/hyperactivity disorder (ADHD) as a risk factor for engagement in violent offending. Despite the link between the disorder and violent offending, this risk factor has yet to be examined as a predictor of heterogeneity in the development of violent offending among juvenile offenders. It is likely that the impulsivity, genetic link, and generally chronic disorder course which are characteristics of the disorder play roles in predicting violent offending, which is consistent with both self-control theory and general developmental theory related to early life deficits and life-course persistent offending. Past research has also elucidated a developmental trajectory model of violent offending, which is utilized by the present research. The present research examines ADHD as a risk factor predicting trajectory group assignment. The Pathways to Desistance data followed 1,354 juvenile offenders for 84 months following conviction for a serious offense. Using multinomial logistic regression, this study extends past research on the development of violent offending among juvenile offenders by examining ADHD as a risk factor predicting assignment to violent offending trajectory groups. Results indicate that meeting criteria for ADHD at baseline predicted membership to all trajectory groups relative to the Abstaining group when all covariates were included. This increase in risk is highest for the trajectory group characterized by the highest frequency of violent offending. This indicates the relevance of identifying and treating ADHD among juvenile offenders to best mitigate risk of violent recidivism throughout adolescence and early adulthood.
Enhancing the Value of Population-Based Risk Scores for Institutional-Level Use.
Raza, Sajjad; Sabik, Joseph F; Rajeswaran, Jeevanantham; Idrees, Jay J; Trezzi, Matteo; Riaz, Haris; Javadikasgari, Hoda; Nowicki, Edward R; Svensson, Lars G; Blackstone, Eugene H
2016-07-01
We hypothesized that factors associated with an institution's residual risk unaccounted for by population-based models may be identifiable and used to enhance the value of population-based risk scores for quality improvement. From January 2000 to January 2010, 4,971 patients underwent aortic valve replacement (AVR), either isolated (n = 2,660) or with concomitant coronary artery bypass grafting (AVR+CABG; n = 2,311). Operative mortality and major morbidity and mortality predicted by The Society of Thoracic Surgeons (STS) risk models were compared with observed values. After adjusting for patients' STS score, additional and refined risk factors were sought to explain residual risk. Differences between STS model coefficients (risk-factor strength) and those specific to our institution were calculated. Observed operative mortality was less than predicted for AVR (1.6% [42 of 2,660] vs 2.8%, p < 0.0001) and AVR+CABG (2.6% [59 of 2,311] vs 4.9%, p < 0.0001). Observed major morbidity and mortality was also lower than predicted for isolated AVR (14.6% [389 of 2,660] vs 17.5%, p < 0.0001) and AVR+CABG (20.0% [462 of 2,311] vs 25.8%, p < 0.0001). Shorter height, higher bilirubin, and lower albumin were identified as additional institution-specific risk factors, and body surface area, creatinine, glomerular filtration rate, blood urea nitrogen, and heart failure across all levels of functional class were identified as refined risk-factor variables associated with residual risk. In many instances, risk-factor strength differed substantially from that of STS models. Scores derived from population-based models can be enhanced for institutional level use by adjusting for institution-specific additional and refined risk factors. Identifying these and measuring differences in institution-specific versus population-based risk-factor strength can identify areas to target for quality improvement initiatives. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
Wang, Yuan; Gao, Ying; Battsend, Munkhzul; Chen, Kexin; Lu, Wenli; Wang, Yaogang
2014-11-01
The optimal approach regarding breast cancer screening for Chinese women is unclear due to the relative low incidence rate. A risk assessment tool may be useful for selection of high-risk subsets of population for mammography screening in low-incidence and resource-limited developing country. The odd ratios for six main risk factors of breast cancer were pooled by review manager after a systematic research of literature. Health risk appraisal (HRA) model was developed to predict an individual's risk of developing breast cancer in the next 5 years from current age. The performance of this HRA model was assessed based on a first-round screening database. Estimated risk of breast cancer increased with age. Increases in the 5-year risk of developing breast cancer were found with the existence of any of included risk factors. When individuals who had risk above median risk (3.3‰) were selected from the validation database, the sensitivity is 60.0% and the specificity is 47.8%. The unweighted area under the curve (AUC) was 0.64 (95% CI = 0.50-0.78). The risk-prediction model reported in this article is based on a combination of risk factors and shows good overall predictive power, but it is still weak at predicting which particular women will develop the disease. It would be very helpful for the improvement of a current model if more population-based prospective follow-up studies were used for the validation.
Koivistoinen, Teemu; Lyytikäinen, Leo-Pekka; Aatola, Heikki; Luukkaala, Tiina; Juonala, Markus; Viikari, Jorma; Lehtimäki, Terho; Raitakari, Olli T; Kähönen, Mika; Hutri-Kähönen, Nina
2018-03-01
The aim of the present study was to examine whether pulse wave velocity (PWV) predicts the progression of blood pressure and the development of hypertension in young adults. In addition, we studied whether PWV improves the risk prediction of incident hypertension beyond traditional cardiovascular risk factors. Systolic and diastolic blood pressures were measured in 2007 and 2011 for 1449 Finnish adults (aged 30-45 years). In addition, PWV and other cardiovascular risk factors were measured in 2007. The association between PWV (in 2007) and blood pressure (in 2011) was studied in the whole population (n=1449) and in a normotensive subpopulation (n=1183). The ability of PWV measured in 2007 to predict incident hypertension in 2011 was investigated in the subpopulation (n=1183). PWV measured in 2007 was directly and independently associated with systolic and diastolic blood pressures measured in 2011 ( P <0.001 for both). PWV measured in 2007 was also an independent predictor of incident hypertension in 2011 (odds ratio, 1.96 per 1-SDincrease; 95% confidence interval, 1.51-2.57; P <0.001). The extended prediction model (including PWV) improved the incident hypertension risk prediction beyond traditional cardiovascular risk factors, the area under receiver operating characteristics curve being 0.833 versus 0.809 ( P =0.040), and the continuous net reclassification improvement 59.4% ( P <0.001). These findings suggest that PWV predicts the progression of blood pressure and could provide a valuable tool in hypertension risk prediction in young adults. © 2018 American Heart Association, Inc.
Road death trend in the United States: implied effects of prevention.
Robertson, Leon
2018-05-01
This study estimates road deaths prevented by U.S. vehicle safety regulations, state laws, and other efforts based on comparison of actual deaths to those predicted from temperature and precipitation effects on exposure, migration to warmer areas, population growth, median age of the population, and vehicle mix. Logistic regression of risk factors predictive of road deaths in 1961, prior to the adoption of federal vehicle safety regulations, state behavioral change laws, and other preventive efforts were used to predict deaths in subsequent years given the changing prevalence of the risk factors from 1962 to 2015. The included risk factors are strong predictors of road death risk. Without the preventive efforts, an additional 5.8 million road deaths would likely have occurred in the U.S. from the initiation of federal safety standards for new vehicles in 1968 through 2015.
Can we predict Acute Medical readmissions using the BOOST tool? A retrospective case note review.
Lee, Geraldine A; Freedman, Daniel; Beddoes, Penelope; Lyness, Emily; Nixon, Imogen; Srivastava, Vivek
2016-01-01
Readmissions within 30-days of hospital discharge are a problem. The aim was to determine if the Better Outcomes for Older Adults through Safe Transitions (BOOST) risk assessment tool was applicable within the UK. Patients over 65 readmitted were identified retrospectively via a casenote review. BOOST assessment was applied with 1 point for each risk factor. 324 patients were readmitted (mean age 77 years) with a median of 7 days between discharge and readmission. The median BOOST score was 3 (IQR 2-4) with polypharmacy evident in 88% and prior hospitalisation in 70%. The tool correctly predicted 90% of readmissions using two or more risk factors and 99.1% if one risk factor was included. The BOOST assessment tool appears appropriate in predicting readmissions however further analysis is required to determine its precision.
Risk and the physics of clinical prediction.
McEvoy, John W; Diamond, George A; Detrano, Robert C; Kaul, Sanjay; Blaha, Michael J; Blumenthal, Roger S; Jones, Steven R
2014-04-15
The current paradigm of primary prevention in cardiology uses traditional risk factors to estimate future cardiovascular risk. These risk estimates are based on prediction models derived from prospective cohort studies and are incorporated into guideline-based initiation algorithms for commonly used preventive pharmacologic treatments, such as aspirin and statins. However, risk estimates are more accurate for populations of similar patients than they are for any individual patient. It may be hazardous to presume that the point estimate of risk derived from a population model represents the most accurate estimate for a given patient. In this review, we exploit principles derived from physics as a metaphor for the distinction between predictions regarding populations versus patients. We identify the following: (1) predictions of risk are accurate at the level of populations but do not translate directly to patients, (2) perfect accuracy of individual risk estimation is unobtainable even with the addition of multiple novel risk factors, and (3) direct measurement of subclinical disease (screening) affords far greater certainty regarding the personalized treatment of patients, whereas risk estimates often remain uncertain for patients. In conclusion, shifting our focus from prediction of events to detection of disease could improve personalized decision-making and outcomes. We also discuss innovative future strategies for risk estimation and treatment allocation in preventive cardiology. Copyright © 2014 Elsevier Inc. All rights reserved.
Mortality determinants and prediction of outcome in high risk newborns.
Dalvi, R; Dalvi, B V; Birewar, N; Chari, G; Fernandez, A R
1990-06-01
The aim of this study was to determine independent patient-related predictors of mortality in high risk newborns admitted at our centre. The study population comprised 100 consecutive newborns each, from the premature unit (PU) and sick baby care unit (SBCU), respectively. Thirteen high risk factors (variables) for each of the two units, were entered into a multivariate regression analysis. Variables with independent predictive value for poor outcome (i.e., death) in PU were, weight less than 1 kg, hyaline membrane disease, neurologic problems, and intravenous therapy. High risk factors in SBCU included, blood gas abnormality, bleeding phenomena, recurrent convulsions, apnea, and congenital anomalies. Identification of these factors guided us in defining priority areas for improvement in our system of neonatal care. Also, based on these variables a simple predictive score for outcome was constructed. The prediction equation and the score were cross-validated by applying them to a 'test-set' of 100 newborns each for PU and SBCU. Results showed a comparable sensitivity, specificity and error rate.
Keltikangas-Järvinen, Liisa; Pulkki-Råback, Laura; Puttonen, Sampsa; Viikari, Jorma; Raitakari, Olli T
2006-01-01
We investigated whether childhood temperament was able to predict carotid artery intima media thickness (IMT) and/or its risk factors in adulthood 21 years later. The subjects were the three youngest age cohorts of the population-based sample of the Cardiovascular Risk in Young Finns study, i.e., those who were aged 3 to 9 years (n = 708) at the baseline. IMT was assessed by ultrasound, and temperament in terms of negative emotionality, hyperactivity, and sociability (following Buss and Plomin). In addition, the levels of traditional risk factors for atherosclerosis were measured in both childhood and adulthood. Childhood temperament was found to predict adulthood risk factors such as smoking in both genders and body mass index (BMI), systolic blood pressure (SBP), and educational level in women. In women, childhood hyperactivity predicted adulthood IMT after adjustment for childhood and adulthood risk factors for atherosclerosis. These findings suggest that temperament may contribute to the development of IMT in two ways: indirectly through risk factors in both genders and in women directly through a mechanism that is not considered in the present study. There were no significant gender-related differences in temperament, but it seemed to play different roles in different genders. Hyperactivity was a greater risk for girls than for boys.
ERIC Educational Resources Information Center
Gijsel, Martine A. R.; Bosman, Anna M. T.; Verhoeven, Ludo
2006-01-01
This study focused on the predictive value of risk factors, cognitive factors, and teachers' judgments in a sample of 462 kindergartners for their early reading skills and reading failure at the beginning of Grade 1. With respect to risk factors, enrollment in speech-language therapy, history of dyslexia or speech-language problems in the family,…
Miovský, Michal; Vonkova, Hana; Čablová, Lenka; Gabrhelík, Roman
2015-11-01
To study the effect of a universal prevention intervention targeting cannabis use in individual children with different risk profiles. A school-based randomized controlled prevention trial was conducted over a period of 33 months (n=1874 sixth-graders, baseline mean age 11.82). We used a two-level random intercept logistic model for panel data to predict the probabilities of cannabis use for each child. Specifically, we used eight risk/protective factors to characterize each child and then predicted two probabilities of cannabis use for each child if the child had the intervention or not. Using the two probabilities, we calculated the absolute and relative effect of the intervention for each child. According to the two probabilities, we also divided the sample into a low-risk group (the quarter of the children with the lowest probabilities), a moderate-risk group, and a high-risk group (the quarter of the children with the highest probabilities) and showed the average effect of the intervention on these groups. The differences between the intervention group and the control group were statistically significant in each risk group. The average predicted probabilities of cannabis use for a child from the low-risk group were 4.3% if the child had the intervention and 6.53% if no intervention was provided. The corresponding probabilities for a child from the moderate-risk group were 10.91% and 15.34% and for a child from the high-risk group 25.51% and 32.61%. School grades, thoughts of hurting oneself, and breaking the rules were the three most important factors distinguishing high-risk and low-risk children. We predicted the effect of the intervention on individual children, characterized by their risk/protective factors. The predicted absolute effect and relative effect of any intervention for any selected risk/protective profile of a given child may be utilized in both prevention practice and research. Copyright © 2015 Elsevier Ltd. All rights reserved.
Toyabe, Shin-ichi
2014-01-01
Inpatient falls are the most common adverse events that occur in a hospital, and about 3 to 10% of falls result in serious injuries such as bone fractures and intracranial haemorrhages. We previously reported that bone fractures and intracranial haemorrhages were two major fall-related injuries and that risk assessment score for osteoporotic bone fracture was significantly associated not only with bone fractures after falls but also with intracranial haemorrhage after falls. Based on the results, we tried to establish a risk assessment tool for predicting fall-related severe injuries in a hospital. Possible risk factors related to fall-related serious injuries were extracted from data on inpatients that were admitted to a tertiary-care university hospital by using multivariate Cox’ s regression analysis and multiple logistic regression analysis. We found that fall risk score and fracture risk score were the two significant factors, and we constructed models to predict fall-related severe injuries incorporating these factors. When the prediction model was applied to another independent dataset, the constructed model could detect patients with fall-related severe injuries efficiently. The new assessment system could identify patients prone to severe injuries after falls in a reproducible fashion. PMID:25168984
Pearce, B.D.; Grove, J.; Bonney, E.A.; Bliwise, N.; Dudley, D.J.; Schendel, D.E.; Thorsen, P.
2010-01-01
Background/Aims To examine the relationship of biological mediators (cytokines, stress hormones), psychosocial, obstetric history, and demographic factors in the early prediction of preterm birth (PTB) using a comprehensive logistic regression model incorporating diverse risk factors. Methods In this prospective case-control study, maternal serum biomarkers were quantified at 9–23 weeks’ gestation in 60 women delivering at <37 weeks compared to 123 women delivering at term. Biomarker data were combined with maternal sociodemographic factors and stress data into regression models encompassing 22 preterm risk factors and 1st-order interactions. Results Among individual biomarkers, we found that macrophage migration inhibitory factor (MIF), interleukin-10, C-reactive protein (CRP), and tumor necrosis factor-α were statistically significant predictors of PTB at all cutoff levels tested (75th, 85th, and 90th percentiles). We fit multifactor models for PTB prediction at each biomarker cutoff. Our best models revealed that MIF, CRP, risk-taking behavior, and low educational attainment were consistent predictors of PTB at all biomarker cutoffs. The 75th percentile cutoff yielded the best predicting model with an area under the ROC curve of 0.808 (95% CI 0.743–0.874). Conclusion Our comprehensive models highlight the prominence of behavioral risk factors for PTB and point to MIF as a possible psychobiological mediator. PMID:20160447
Pearce, B D; Grove, J; Bonney, E A; Bliwise, N; Dudley, D J; Schendel, D E; Thorsen, P
2010-01-01
To examine the relationship of biological mediators (cytokines, stress hormones), psychosocial, obstetric history, and demographic factors in the early prediction of preterm birth (PTB) using a comprehensive logistic regression model incorporating diverse risk factors. In this prospective case-control study, maternal serum biomarkers were quantified at 9-23 weeks' gestation in 60 women delivering at <37 weeks compared to 123 women delivering at term. Biomarker data were combined with maternal sociodemographic factors and stress data into regression models encompassing 22 preterm risk factors and 1st-order interactions. Among individual biomarkers, we found that macrophage migration inhibitory factor (MIF), interleukin-10, C-reactive protein (CRP), and tumor necrosis factor-alpha were statistically significant predictors of PTB at all cutoff levels tested (75th, 85th, and 90th percentiles). We fit multifactor models for PTB prediction at each biomarker cutoff. Our best models revealed that MIF, CRP, risk-taking behavior, and low educational attainment were consistent predictors of PTB at all biomarker cutoffs. The 75th percentile cutoff yielded the best predicting model with an area under the ROC curve of 0.808 (95% CI 0.743-0.874). Our comprehensive models highlight the prominence of behavioral risk factors for PTB and point to MIF as a possible psychobiological mediator. Copyright (c) 2010 S. Karger AG, Basel.
USDA-ARS?s Scientific Manuscript database
There are limited data available on the longitudinal relationship between candy consumption by children on weight and other cardiovascular risk factors (CVRF) in young adults. The present study investigated whether candy consumption in children was predictive of weight and CVRF in young adults. A lo...
Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status.
Hüsing, Anika; Canzian, Federico; Beckmann, Lars; Garcia-Closas, Montserrat; Diver, W Ryan; Thun, Michael J; Berg, Christine D; Hoover, Robert N; Ziegler, Regina G; Figueroa, Jonine D; Isaacs, Claudine; Olsen, Anja; Viallon, Vivian; Boeing, Heiner; Masala, Giovanna; Trichopoulos, Dimitrios; Peeters, Petra H M; Lund, Eiliv; Ardanaz, Eva; Khaw, Kay-Tee; Lenner, Per; Kolonel, Laurence N; Stram, Daniel O; Le Marchand, Loïc; McCarty, Catherine A; Buring, Julie E; Lee, I-Min; Zhang, Shumin; Lindström, Sara; Hankinson, Susan E; Riboli, Elio; Hunter, David J; Henderson, Brian E; Chanock, Stephen J; Haiman, Christopher A; Kraft, Peter; Kaaks, Rudolf
2012-09-01
There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumours with different hormone receptor status. Within the Breast and Prostate Cancer Cohort Consortium, we analysed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age adjusted and cohort-adjusted concordance statistic (AUROC(a)). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement was used to measure improvements in risk prediction. We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROC(a) going from 2.7% to 4%). Discriminatory ability for all models varied strongly by hormone receptor status. Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor-positive cases, but the gain in discriminatory quality is not sufficient for clinical application.
Risk factors for lung function decline in a large cohort of young cystic fibrosis patients.
Cogen, Jonathan; Emerson, Julia; Sanders, Don B; Ren, Clement; Schechter, Michael S; Gibson, Ronald L; Morgan, Wayne; Rosenfeld, Margaret
2015-08-01
To identify novel risk factors and corroborate previously identified risk factors for mean annual decline in FEV1% predicted in a large, contemporary, United States cohort of young cystic fibrosis (CF) patients. Retrospective observational study of participants in the EPIC Observational Study, who were Pseudomonas-negative and ≤12 years of age at enrollment in 2004-2006. The associations between potential demographic, clinical, and environmental risk factors evaluated during the baseline year and subsequent mean annual decline in FEV1 percent predicted were evaluated using generalized estimating equations. The 946 participants in the current analysis were followed for a mean of 6.2 (SD 1.3) years. Mean annual decline in FEV1% predicted was 1.01% (95%CI 0.85-1.17%). Children with one or no F508del mutations had a significantly smaller annual decline in FEV1 compared to F508del homozygotes. In a multivariable model, risk factors during the baseline year associated with a larger subsequent mean annual lung function decline included female gender, frequent or productive cough, low BMI (<66th percentile, median in the cohort), ≥1 pulmonary exacerbation, high FEV1 (≥115% predicted, in the top quartile), and respiratory culture positive for methicillin-sensitive Staphylococcus aureus, methicillin-resistant S. aureus, or Stenotrophomonas maltophilia. We have identified a range of risk factors for FEV1 decline in a large cohort of young, CF patients who were Pa negative at enrollment, including novel as well as previously identified characteristics. These results could inform the design of a clinical trial in which rate of FEV1 decline is the primary endpoint and identify high-risk groups that may benefit from closer monitoring. © 2015 Wiley Periodicals, Inc.
Ferrer, Rebecca A; Klein, William M P; Persoskie, Alexander; Avishai-Yitshak, Aya; Sheeran, Paschal
2016-10-01
Although risk perception is a key predictor in health behavior theories, current conceptions of risk comprise only one (deliberative) or two (deliberative vs. affective/experiential) dimensions. This research tested a tripartite model that distinguishes among deliberative, affective, and experiential components of risk perception. In two studies, and in relation to three common diseases (cancer, heart disease, diabetes), we used confirmatory factor analyses to examine the factor structure of the tripartite risk perception (TRIRISK) model and compared the fit of the TRIRISK model to dual-factor and single-factor models. In a third study, we assessed concurrent validity by examining the impact of cancer diagnosis on (a) levels of deliberative, affective, and experiential risk perception, and (b) the strength of relations among risk components, and tested predictive validity by assessing relations with behavioral intentions to prevent cancer. The tripartite factor structure was supported, producing better model fit across diseases (studies 1 and 2). Inter-correlations among the components were significantly smaller among participants who had been diagnosed with cancer, suggesting that affected populations make finer-grained distinctions among risk perceptions (study 3). Moreover, all three risk perception components predicted unique variance in intentions to engage in preventive behavior (study 3). The TRIRISK model offers both a novel conceptualization of health-related risk perceptions, and new measures that enhance predictive validity beyond that engendered by unidimensional and bidimensional models. The present findings have implications for the ways in which risk perceptions are targeted in health behavior change interventions, health communications, and decision aids.
Examining Overgeneral Autobiographical Memory as a Risk Factor for Adolescent Depression
ERIC Educational Resources Information Center
Rawal, Adhip; Rice, Frances
2012-01-01
Objective: Identifying risk factors for adolescent depression is an important research aim. Overgeneral autobiographical memory (OGM) is a feature of adolescent depression and a candidate cognitive risk factor for future depression. However, no study has ascertained whether OGM predicts the onset of adolescent depressive disorder. OGM was…
ERIC Educational Resources Information Center
Pfaff, Jann
2013-01-01
Defining fall risk factors and predicting fall risk status among patients in acute care has been a topic of research for decades. With increasing pressure on hospitals to provide quality care and prevent hospital-acquired conditions, the search for effective fall prevention interventions continues. Hundreds of risk factors for falls in acute care…
Risk and Protective Factors Influencing Life Skills among Youths in Long-Term Foster Care.
ERIC Educational Resources Information Center
Nollan, K. A.; Pecora, P. J.; Nurius, P. N.; Whittaker, J. K.
2002-01-01
Examined through mail surveys of youth, parents, and social workers the predictive value of selected risk and protective factors in explaining self-sufficiency skills of 219 ethnically diverse 12- to 15-year-olds in foster care. Found that protective factors related to greater self-sufficiency skills, and risk factors were negatively associated.…
Visscher, H; Ross, C J D; Rassekh, S R; Sandor, G S S; Caron, H N; van Dalen, E C; Kremer, L C; van der Pal, H J; Rogers, P C; Rieder, M J; Carleton, B C; Hayden, M R
2013-08-01
The use of anthracyclines as effective antineoplastic drugs is limited by the occurrence of cardiotoxicity. Multiple genetic variants predictive of anthracycline-induced cardiotoxicity (ACT) in children were recently identified. The current study was aimed to assess replication of these findings in an independent cohort of children. . Twenty-three variants were tested for association with ACT in an independent cohort of 218 patients. Predictive models including genetic and clinical risk factors were constructed in the original cohort and assessed in the current replication cohort. . We confirmed the association of rs17863783 in UGT1A6 and ACT in the replication cohort (P = 0.0062, odds ratio (OR) 7.98). Additional evidence for association of rs7853758 (P = 0.058, OR 0.46) and rs885004 (P = 0.058, OR 0.42) in SLC28A3 was found (combined P = 1.6 × 10(-5) and P = 3.0 × 10(-5), respectively). A previously constructed prediction model did not significantly improve risk prediction in the replication cohort over clinical factors alone. However, an improved prediction model constructed using replicated genetic variants as well as clinical factors discriminated significantly better between cases and controls than clinical factors alone in both original (AUC 0.77 vs. 0.68, P = 0.0031) and replication cohort (AUC 0.77 vs. 0.69, P = 0.060). . We validated genetic variants in two genes predictive of ACT in an independent cohort. A prediction model combining replicated genetic variants as well as clinical risk factors might be able to identify high- and low-risk patients who could benefit from alternative treatment options. Copyright © 2013 Wiley Periodicals, Inc.
Mikolajczak, Moïra; Roskam, Isabelle
2018-01-01
Parental burnout is a specific syndrome resulting from enduring exposure to chronic parenting stress. But why do some parents burn out while others, facing the same stressors, do not? The main aim of this paper was to propose a theory of parental burnout capable of predicting who is at risk of burnout, explaining why a particular parent burned out and why at that specific point in time, and providing directions for intervention. The secondary goal was to operationalize this theory in a tool that would be easy to use for both researchers and clinicians. The results of this two-wave longitudinal study conducted on 923 parents suggest that the Balance between Risks and Resources (BR2) theory proposed here is a relevant framework to predict and explain parental burnout. More specifically, the results show that (1) the BR2 instrument reliably measures parents' balance between risks (parental stress-enhancing factors) and resources (parental stress-alleviating factors), (2) there is a strong linear relationship between BR2 score and parental burnout, (3) parental burnout results from a chronic imbalance of risks over resources, (4) BR2 predicts parental burnout better than job burnout and (5) among the risk and resource factors measured in BR2, risks and resources non-specific to parenting (e.g., low stress-management abilities, perfectionism) equally predict parental and job burnout, while risks and resources specific to parenting (e.g., childrearing practices, coparenting) uniquely predict parental burnout. PMID:29946278
Jin, Shuo; Shi, Xiao-Ju; Sun, Xiao-Dong; Zhang, Ping; Lv, Guo-Yue; Du, Xiao-Hong; Wang, Si-Yuan; Wang, Guang-Yi
2015-01-01
Abstract This article aims to identify risk factors for postoperative pancreatic fistula (POPF) and evaluate the gastric/pancreatic amylase ratio (GPAR) on postoperative day (POD) 3 as a POPF predictor in patients who undergo pancreaticoduodenectomy (PD). POPF significantly contributes to mortality and morbidity in patients who undergo PD. Previously identified predictors for POPF often have low predictive accuracy. Therefore, accurate POPF predictors are needed. In this prospective cohort study, we measured the clinical and biochemical factors of 61 patients who underwent PD and diagnosed POPF according to the definition of the International Study Group of Pancreatic Fistula. We analyzed the association between POPF and various factors, identified POPF risk factors, and evaluated the predictive power of the GPAR on POD3 and the levels of serum and ascites amylase. Of the 61 patients, 21 developed POPF. The color of the pancreatic drain fluid, POD1 serum, POD1 median output of pancreatic drain fluid volume, and GPAR were significantly associated with POPF. The color of the pancreatic drain fluid and high GPAR were independent risk factors. Although serum and ascites amylase did not predict POPF accurately, the cutoff value was 1.24, and GPAR predicted POPF with high sensitivity and specificity. This is the first report demonstrating that high GPAR on POD3 is a risk factor for POPF and showing that GPAR is a more accurate predictor of POPF than the previously reported amylase markers. PMID:25621676
Jin, Shuo; Shi, Xiao-Ju; Sun, Xiao-Dong; Zhang, Ping; Lv, Guo-Yue; Du, Xiao-Hong; Wang, Si-Yuan; Wang, Guang-Yi
2015-01-01
This article aims to identify risk factors for postoperative pancreatic fistula (POPF) and evaluate the gastric/pancreatic amylase ratio (GPAR) on postoperative day (POD) 3 as a POPF predictor in patients who undergo pancreaticoduodenectomy (PD).POPF significantly contributes to mortality and morbidity in patients who undergo PD. Previously identified predictors for POPF often have low predictive accuracy. Therefore, accurate POPF predictors are needed.In this prospective cohort study, we measured the clinical and biochemical factors of 61 patients who underwent PD and diagnosed POPF according to the definition of the International Study Group of Pancreatic Fistula. We analyzed the association between POPF and various factors, identified POPF risk factors, and evaluated the predictive power of the GPAR on POD3 and the levels of serum and ascites amylase.Of the 61 patients, 21 developed POPF. The color of the pancreatic drain fluid, POD1 serum, POD1 median output of pancreatic drain fluid volume, and GPAR were significantly associated with POPF. The color of the pancreatic drain fluid and high GPAR were independent risk factors. Although serum and ascites amylase did not predict POPF accurately, the cutoff value was 1.24, and GPAR predicted POPF with high sensitivity and specificity.This is the first report demonstrating that high GPAR on POD3 is a risk factor for POPF and showing that GPAR is a more accurate predictor of POPF than the previously reported amylase markers.
Clusters of Behaviors and Beliefs Predicting Adolescent Depression: Implications for Prevention
Paunesku, David; Ellis, Justin; Fogel, Joshua; Kuwabara, Sachiko A; Gollan, Jackie; Gladstone, Tracy; Reinecke, Mark; Van Voorhees, Benjamin W.
2009-01-01
OBJECTIVE Risk factors for various disorders are known to cluster. However, the factor structure for behaviors and beliefs predicting depressive disorder in adolescents is not known. Knowledge of this structure can facilitate prevention planning. METHODS We used the National Longitudinal Study of Adolescent Health (AddHealth) data set to conduct an exploratory factor analysis to identify clusters of behaviors/experiences predicting the onset of major depressive disorder (MDD) at 1-year follow-up (N=4,791). RESULTS Four factors were identified: family/interpersonal relations, self-emancipation, avoidant problem solving/low self-worth, and religious activity. Strong family/interpersonal relations were the most significantly protective against depression at one year follow-up. Avoidant problem solving/low self-worth was not predictive of MDD on its own, but significantly amplified the risks associated with delinquency. CONCLUSION Depression prevention interventions should consider giving family relationships a more central role in their efforts. Programs teaching problem solving skills may be most appropriate for reducing MDD risk in delinquent youth. PMID:20502621
Personality patterns predict the risk of antisocial behavior in Spanish-speaking adolescents.
Alcázar-Córcoles, Miguel A; Verdejo-García, Antonio; Bouso-Sáiz, José C; Revuelta-Menéndez, Javier; Ramírez-Lira, Ezequiel
2017-05-01
There is a renewed interest in incorporating personality variables in criminology theories in order to build models able to integrate personality variables and biological factors with psychosocial and sociocultural factors. The aim of this article is the assessment of personality dimensions that contribute to the prediction of antisocial behavior in adolescents. For this purpose, a sample of adolescents from El Salvador, Mexico, and Spain was obtained. The sample consisted of 1035 participants with a mean age of 16.2. There were 450 adolescents from a forensic population (those who committed a crime) and 585 adolescents from the normal population (no crime committed). All of participants answered personality tests about neuroticism, extraversion, psychoticism, sensation seeking, impulsivity, and violence risk. Principal component analysis of the data identified two independent factors: (i) the disinhibited behavior pattern (PDC), formed by the dimensions of neuroticism, psychoticism, impulsivity and risk of violence; and (ii) the extrovert behavior pattern (PEC), formed by the dimensions of sensation risk and extraversion. Both patterns significantly contributed to the prediction of adolescent antisocial behavior in a logistic regression model which properly classifies a global percentage of 81.9%, 86.8% for non-offense and 72.5% for offense behavior. The classification power of regression equations allows making very satisfactory predictions about adolescent offense commission. Educational level has been classified as a protective factor, while age and gender (male) have been classified as risk factors.
A Comparison of Birth Outcomes Among Black, Hispanic, and Black Hispanic Women
BeLue, Rhonda; Hillemeier, Marianne M.
2015-01-01
Background While non-Hispanic Black populations tend to be disproportionately affected by adverse reproductive outcomes, Hispanic populations tend to demonstrate healthier birth outcomes, regardless of socioeconomic background. Little is known about birth outcomes for women who are both Black and Hispanic. We examined whether birth outcomes and risk factors for women who are both Black and Hispanic most closely resemble those of women who are only Black or Hispanic and also compared these outcomes to those for Whites. Methods Using the 2013 US natality files, we examined 2,970,315 singleton births to Black Hispanic, Hispanic, Black, and White mothers. We used logistic regression to calculate predicted probabilities of low birth weight (LBW), preterm birth (PTB), or small for gestational age (SGA). Race-stratified regression analysis was used to identify the factors that significantly predicted risk for each outcome for each racial/ethnic group. Results Black mothers had the highest prevalence and predicted probabilities of experiencing all three outcomes. Black Hispanic mothers were less likely than Black mothers and more likely than Hispanic mothers to experience each of the adverse outcomes. We also found support for racial variation in risk and protective factors for mothers in the different groups. Factors like age and education inconsistently predicted risk of experiencing the birth outcomes for all groups. Overall, Black Hispanic mothers had birth outcomes and risk factor profiles like Hispanic mothers, although they had sociodemographic characteristics and health behaviors like Black mothers. Conclusions Patterning of birth outcomes among Black Hispanic women suggest an intersection of risk and protective factors associated with their respective racial and ethnic identities. Additional information about sociodemographic context is needed to develop a more complete picture of how factors related to race and ethnic group membership influence Black Hispanic women’s birth outcomes. PMID:26561541
O'Shea, Laura E; Picchioni, Marco M; Dickens, Geoffrey L
2016-04-01
The Short-Term Assessment of Risk and Treatability (START) aims to assist mental health practitioners to estimate an individual's short-term risk for a range of adverse outcomes via structured consideration of their risk ("Vulnerabilities") and protective factors ("Strengths") in 20 areas. It has demonstrated predictive validity for aggression but this is less established for other outcomes. We collated START assessments for N = 200 adults in a secure mental health hospital and ascertained 3-month risk event incidence using the START Outcomes Scale. The specific risk estimates, which are the tool developers' suggested method of overall assessment, predicted aggression, self-harm/suicidality, and victimization, and had incremental validity over the Strength and Vulnerability scales for these outcomes. The Strength scale had incremental validity over the Vulnerability scale for aggressive outcomes; therefore, consideration of protective factors had demonstrable value in their prediction. Further evidence is required to support use of the START for the full range of outcomes it aims to predict. © The Author(s) 2015.
Li, Hai-Yan; Guo, Yu-Tao; Tian, Cui; Song, Chao-Qun; Mu, Yang; Li, Yang; Chen, Yun-Dai
2017-08-01
The vasovagal reflex syndrome (VVRS) is common in the patients undergoing percutaneous coronary intervention (PCI). However, prediction and prevention of the risk for the VVRS have not been completely fulfilled. This study was conducted to develop a Risk Prediction Score Model to identify the determinants of VVRS in a large Chinese population cohort receiving PCI. From the hospital electronic medical database, we identified 3550 patients who received PCI (78.0% males, mean age 60 years) in Chinese PLA General Hospital from January 1, 2000 to August 30, 2016. The multivariate analysis and receiver operating characteristic (ROC) analysis were performed. The adverse events of VVRS in the patients were significantly increased after PCI procedure than before the operation (all P < 0.001). The rate of VVRS [95% confidence interval (CI)] in patients receiving PCI was 4.5% (4.1%-5.6%). Compared to the patients suffering no VVRS, incidence of VVRS involved the following factors, namely female gender, primary PCI, hypertension, over two stents implantation in the left anterior descending (LAD), and the femoral puncture site. The multivariate analysis suggested that they were independent risk factors for predicting the incidence of VVRS (all P < 0.001). We developed a risk prediction score model for VVRS. ROC analysis showed that the risk prediction score model was effectively predictive of the incidence of VVRS in patients receiving PCI (c-statistic 0.76, 95% CI: 0.72-0.79, P < 0.001). There were decreased events of VVRS in the patients receiving PCI whose diastolic blood pressure dropped by more than 30 mmHg and heart rate reduced by 10 times per minute (AUC: 0.84, 95% CI: 0.81-0.87, P < 0.001). The risk prediction score is quite efficient in predicting the incidence of VVRS in patients receiving PCI. In which, the following factors may be involved, the femoral puncture site, female gender, hypertension, primary PCI, and over 2 stents implanted in LAD.
Developmental dyslexia: predicting individual risk
Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J
2015-01-01
Background Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. Methods The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as ‘dyslexic’ or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Results Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Conclusions Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. PMID:25832320
Hope as a Predictor of Interpersonal Suicide Risk
ERIC Educational Resources Information Center
Davidson, Collin L.; Wingate, LaRicka R.; Rasmussen, Kathy A.; Slish, Meredith L.
2009-01-01
The current study hypothesized that (1) hope would negatively predict burdensomeness, thwarted belongingness, and acquired capability to enact lethal injury; (2) hope would negatively predict suicidal ideation; and (3) the interpersonal suicide risk factors would predict suicidal ideation. Results indicated that hope negatively predicted…
Risk Factors and Biomarkers of Age-Related Macular Degeneration
Lambert, Nathan G.; Singh, Malkit K.; ElShelmani, Hanan; Mansergh, Fiona C.; Wride, Michael A.; Padilla, Maximilian; Keegan, David; Hogg, Ruth E.; Ambati, Balamurali K.
2016-01-01
A biomarker can be a substance or structure measured in body parts, fluids or products that can affect or predict disease incidence. As age-related macular degeneration (AMD) is the leading cause of blindness in the developed world, much research and effort has been invested in the identification of different biomarkers to predict disease incidence, identify at risk individuals, elucidate causative pathophysiological etiologies, guide screening, monitoring and treatment parameters, and predict disease outcomes. To date, a host of genetic, environmental, proteomic, and cellular targets have been identified as both risk factors and potential biomarkers for AMD. Despite this, their use has been confined to research settings and has not yet crossed into the clinical arena. A greater understanding of these factors and their use as potential biomarkers for AMD can guide future research and clinical practice. This article will discuss known risk factors and novel, potential biomarkers of AMD in addition to their application in both academic and clinical settings. PMID:27156982
Myers, J E; Kenny, L C; McCowan, L M E; Chan, E H Y; Dekker, G A; Poston, L; Simpson, N A B; North, R A
2013-09-01
To assess the performance of clinical risk factors, uterine artery Doppler and angiogenic markers to predict preterm pre-eclampsia in nulliparous women. Predictive test accuracy study. Prospective multicentre cohort study Screening for Pregnancy Endpoints (SCOPE). Low-risk nulliparous women with a singleton pregnancy were recruited. Clinical risk factor data were obtained and plasma placental growth factor (PlGF), soluble endoglin and soluble fms-like tyrosine kinase-1 (sFlt-1) were measured at 14-16 weeks of gestation. Prediction models were developed using multivariable stepwise logistic regression. Preterm pre-eclampsia (delivered before 37(+0) weeks of gestation). Of the 3529 women recruited, 187 (5.3%) developed pre-eclampsia of whom 47 (1.3%) delivered preterm. Controls (n = 188) were randomly selected from women without preterm pre-eclampsia and included women who developed other pregnancy complications. An area under a receiver operating characteristic curve (AUC) of 0.76 (95% CI 0.67-0.84) was observed using previously reported clinical risk variables. The AUC improved following the addition of PlGF measured at 14-16 weeks (0.84; 95% CI 0.77-0.91), but no further improvement was observed with the addition of uterine artery Doppler or the other angiogenic markers. A sensitivity of 45% (95% CI 0.31-0.59) (5% false-positive rate) and post-test probability of 11% (95% CI 9-13) were observed using clinical risk variables and PlGF measurement. Addition of plasma PlGF at 14-16 weeks of gestation to clinical risk assessment improved the identification of nulliparous women at increased risk of developing preterm pre-eclampsia, but the performance is not sufficient to warrant introduction as a clinical screening test. These findings are marker dependent, not assay dependent; additional markers are needed to achieve clinical utility. © 2013 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2013 RCOG.
Fetal Substance Exposure and Cumulative Environmental Risk in an African American Cohort
ERIC Educational Resources Information Center
Yumoto, Chie; Jacobson, Sandra W.; Jacobson, Joseph L.
2008-01-01
Two models of vulnerability to socioenvironmental risk were examined in 337 African American children (M = 7.8 years) recruited to overrepresent prenatal alcohol or cocaine exposure: The cumulative risk model predicted synergistic effects from exposure to multiple risk factors, and the fetal patterning of disease model predicted that prenatal…
Discriminative value of FRAX for fracture prediction in a cohort of Chinese postmenopausal women.
Cheung, E Y N; Bow, C H; Cheung, C L; Soong, C; Yeung, S; Loong, C; Kung, A
2012-03-01
We followed 2,266 postmenopausal Chinese women for 4.5 years to determine which model best predicts osteoporotic fracture. A model that contains ethnic-specific risk factors, some of which reflect frailty, performed as well as or better than the well-established FRAX model. Clinical risk assessment, with or without T-score, can predict fractures in Chinese postmenopausal women although it is unknown which combination of clinical risk factors is most effective. This prospective study sought to compare the accuracy for fracture prediction using various models including FRAX, our ethnic-specific clinical risk factors (CRF) and other simple models. This study is part of the Hong Kong Osteoporosis Study. A total of 2,266 treatment naïve postmenopausal women underwent clinical risk factor and bone mineral density assessment. Subjects were followed up for outcome of major osteoporotic fracture and receiver operating characteristic (ROC) curves for different models were compared. The percentage of subjects in different quartiles of risk according to various models who actually fractured was also compared. The mean age at baseline was 62.1 ± 8.5 years and mean follow-up time was 4.5 ± 2.8 years. A total of 106 new major osteoporotic fractures were reported, of which 21 were hip fractures. Ethnic-specific CRF with T-score performed better than FRAX with T-score (based on both Chinese normative and National Health and Nutrition Examination Survey (NHANES) databases) in terms of AUC comparison for prediction of major osteoporotic fracture. The two models were similar in hip fracture prediction. The ethnic-specific CRF model had a 10% higher sensitivity than FRAX at a specificity of 0.8 or above. CRF related to frailty and differences in lifestyle between populations are likely to be important in fracture prediction. Further work is required to determine which and how CRF can be applied to develop a fracture prediction model in our population.
Ingram, Emily R; Robertson, Iain K; Ogden, Kathryn J; Dennis, Amanda E; Campbell, Joanne E; Corbould, Anne M
2017-06-01
Gestational diabetes mellitus (GDM) is associated with life-long increased risk of type 2 diabetes: affected women are advised to undergo oral glucose tolerance testing (OGTT) at 6-12 weeks postpartum, then glucose screening every 1-3 years. We investigated whether in women with GDM, antenatal clinical factors predicted postpartum abnormal glucose tolerance and compliance with screening. In women with GDM delivering 2007 to mid-2009 in a single hospital, antenatal/obstetric data and glucose tests at 6-12 weeks postpartum and during 5.5 years post-pregnancy were retrospectively collected. Predictors of return for testing and abnormal glucose tolerance were identified using multivariate analysis. Of 165 women, 117 (70.9%) returned for 6-12 week postpartum OGTT: 23 (19.6%) were abnormal. Smoking and parity, independent of socioeconomic status, were associated with non-return for testing. Fasting glucose ≥5.4 mmol/L on pregnancy OGTT predicted both non-return for testing and abnormal OGTT. During 5.5 years post-pregnancy, 148 (89.7%) women accessed glucose screening: nine (6.1%) developed diabetes, 33 (22.3%) had impaired fasting glucose / impaired glucose tolerance. Predictors of abnormal glucose tolerance were fasting glucose ≥5.4 mmol/L and 2-h glucose ≥9.3 mmol/L on pregnancy OGTT (~2.5-fold increased risk), and polycystic ovary syndrome (~3.4 fold increased risk). Risk score calculation, based on combined antenatal factors, did not improve predictions. Antenatal clinical factors were modestly predictive of return for testing and abnormal glucose tolerance post-pregnancy in women with GDM. Risk score calculations were ineffective in predicting outcomes: risk scores developed in other populations require validation. Ongoing glucose screening is indicated for all women with GDM. © 2016 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.
Multi-system influences on adolescent risky sexual behavior.
Chen, Angela Chia-Chen; Thompson, Elaine Adams; Morrison-Beedy, Dianne
2010-12-01
We examined multi-system influences on risky sexual behavior measured by cumulative sexual risk index and number of nonromantic sexual partners among 4,465 single, sexually experienced adolescents. Hierarchical Poisson regression analyses were conducted with Wave I-II data from the National Longitudinal Study of Adolescent Health. Individual and family factors predicted both outcome measures. Neighborhood set predicted cumulative sexual risk index only, and peer factors predicted the number of nonromantic sexual partners only. School set did not predict either outcome. There were significant associations among risky sexual behavior, drug use, and delinquent behaviors. The results highlight the need for multifaceted prevention programs that address relevant factors related to family, peer and neighborhood influence as well as individual factors among sexually active adolescents. Copyright © 2010 Wiley Periodicals, Inc.
Early risk factors for criminal offending in schizophrenia: a 35-year longitudinal cohort study.
Eriksson, Asa; Romelsjö, Anders; Stenbacka, Marlene; Tengström, Anders
2011-09-01
Recent evidence suggests that factors predicting offending among individuals with no mental disorder may also predict offending among individuals with schizophrenia. The aims of the study were (1) to explore the prevalence of risk factors for criminal offending reported at age 18 among males later diagnosed with schizophrenia, (2) to explore the associations between risk factors reported at age 18 and lifetime criminal offending, (3) to predict lifetime serious violent offending based on risk factors reported at age 18, and (4) to compare the findings with those in males with no later diagnosis of schizophrenia. The study was a prospective, longitudinal study of a birth cohort followed up through registers after 35 years. The cohort consisted of 49,398 males conscripted into the Swedish Army in 1969-1970, of whom 377 were later diagnosed with schizophrenia. Among the subjects later diagnosed with schizophrenia, strong associations were found between four of the items reported at age 18 and lifetime criminal offending: (1) low marks for conduct in school, (2) contact with the police or child care authorities, (3) crowded living conditions, and (4) arrest for public drinking. Three of these four risk factors were found to double the risk of offending among males with no later diagnosis of schizophrenia. Criminality in individuals with schizophrenia may at least partly be understood as a phenomenon similar to criminality in individuals in the general population.
Novel Biomarkers to Improve the Prediction of Cardiovascular Event Risk in Type 2 Diabetes Mellitus.
van der Leeuw, Joep; Beulens, Joline W J; van Dieren, Susan; Schalkwijk, Casper G; Glatz, Jan F C; Hofker, Marten H; Verschuren, W M Monique; Boer, Jolanda M A; van der Graaf, Yolanda; Visseren, Frank L J; Peelen, Linda M; van der Schouw, Yvonne T
2016-05-31
We evaluated the ability of 23 novel biomarkers representing several pathophysiological pathways to improve the prediction of cardiovascular event (CVE) risk in patients with type 2 diabetes mellitus beyond traditional risk factors. We used data from 1002 patients with type 2 diabetes mellitus from the Second Manifestations of ARTertial disease (SMART) study and 288 patients from the European Prospective Investigation into Cancer and Nutrition-NL (EPIC-NL). The associations of 23 biomarkers (adiponectin, C-reactive protein, epidermal-type fatty acid binding protein, heart-type fatty acid binding protein, basic fibroblast growth factor, soluble FMS-like tyrosine kinase-1, soluble intercellular adhesion molecule-1 and -3, matrix metalloproteinase [MMP]-1, MMP-3, MMP-9, N-terminal prohormone of B-type natriuretic peptide, osteopontin, osteonectin, osteocalcin, placental growth factor, serum amyloid A, E-selectin, P-selectin, tissue inhibitor of MMP-1, thrombomodulin, soluble vascular cell adhesion molecule-1, and vascular endothelial growth factor) with CVE risk were evaluated by using Cox proportional hazards analysis adjusting for traditional risk factors. The incremental predictive performance was assessed with use of the c-statistic and net reclassification index (NRI; continuous and based on 10-year risk strata 0-10%, 10-20%, 20-30%, >30%). A multimarker model was constructed comprising those biomarkers that improved predictive performance in both cohorts. N-terminal prohormone of B-type natriuretic peptide, osteopontin, and MMP-3 were the only biomarkers significantly associated with an increased risk of CVE and improved predictive performance in both cohorts. In SMART, the combination of these biomarkers increased the c-statistic with 0.03 (95% CI 0.01-0.05), and the continuous NRI was 0.37 (95% CI 0.21-0.52). In EPIC-NL, the multimarker model increased the c-statistic with 0.03 (95% CI 0.00-0.03), and the continuous NRI was 0.44 (95% CI 0.23-0.66). Based on risk strata, the NRI was 0.12 (95% CI 0.03-0.21) in SMART and 0.07 (95% CI -0.04-0.17) in EPIC-NL. Of the 23 evaluated biomarkers from different pathophysiological pathways, N-terminal prohormone of B-type natriuretic peptide, osteopontin, MMP-3, and their combination improved CVE risk prediction in 2 separate cohorts of patients with type 2 diabetes mellitus beyond traditional risk factors. However, the number of patients reclassified to a different risk stratum was limited. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.
Risk terrain modeling predicts child maltreatment.
Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye
2016-12-01
As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Chang, Xuling; Salim, Agus; Dorajoo, Rajkumar; Han, Yi; Khor, Chiea-Chuen; van Dam, Rob M; Yuan, Jian-Min; Koh, Woon-Puay; Liu, Jianjun; Goh, Daniel Yt; Wang, Xu; Teo, Yik-Ying; Friedlander, Yechiel; Heng, Chew-Kiat
2017-01-01
Background Although numerous phenotype based equations for predicting risk of 'hard' coronary heart disease are available, data on the utility of genetic information for such risk prediction is lacking in Chinese populations. Design Case-control study nested within the Singapore Chinese Health Study. Methods A total of 1306 subjects comprising 836 men (267 incident cases and 569 controls) and 470 women (128 incident cases and 342 controls) were included. A Genetic Risk Score comprising 156 single nucleotide polymorphisms that have been robustly associated with coronary heart disease or its risk factors ( p < 5 × 10 -8 ) in at least two independent cohorts of genome-wide association studies was built. For each gender, three base models were used: recalibrated Adult Treatment Panel III (ATPIII) Model (M 1 ); ATP III model fitted using Singapore Chinese Health Study data (M 2 ) and M 3 : M 2 + C-reactive protein + creatinine. Results The Genetic Risk Score was significantly associated with incident 'hard' coronary heart disease ( p for men: 1.70 × 10 -10 -1.73 × 10 -9 ; p for women: 0.001). The inclusion of the Genetic Risk Score in the prediction models improved discrimination in both genders (c-statistics: 0.706-0.722 vs. 0.663-0.695 from base models for men; 0.788-0.790 vs. 0.765-0.773 for women). In addition, the inclusion of the Genetic Risk Score also improved risk classification with a net gain of cases being reclassified to higher risk categories (men: 12.4%-16.5%; women: 10.2% (M 3 )), while not significantly reducing the classification accuracy in controls. Conclusions The Genetic Risk Score is an independent predictor for incident 'hard' coronary heart disease in our ethnic Chinese population. Inclusion of genetic factors into coronary heart disease prediction models could significantly improve risk prediction performance.
Fisher, Brian T; Robinson, Paula D; Lehrnbecher, Thomas; Steinbach, William J; Zaoutis, Theoklis E; Phillips, Bob; Sung, Lillian
2017-05-26
Although a number of risk factors have been associated with invasive fungal disease (IFD), a systematic review of the literature to document pediatric-specific factors has not been performed. We used the Ovid SP platform to search Medline, Medline In-Process, and Embase for studies that identified risk factors for IFD in children with cancer or those who undergo hematopoietic stem cell transplantation (HSCT). We included studies if they consisted of children or adolescents (<25 years) who were receiving treatment for cancer or undergoing HSCT and if the study evaluated risk factors among patients with and those without IFD. Among the 3566 studies screened, 22 studies were included. A number of pediatric factors commonly associated with an increased risk for IFD were confirmed, including prolonged neutropenia, high-dose steroid exposure, intensive-timing chemotherapy for acute myeloid leukemia, and acute and chronic graft-versus-host disease. Increasing age, a factor not commonly associated with IFD risk, was identified as a risk factor in multiple published cohorts. With this systematic review, we have confirmed IFD risk factors that are considered routinely in daily clinical practice. Increasing age should also be considered when assessing patient risk for IFD. Future efforts should focus on defining more precise thresholds for a particular risk factor (ie, age, neutropenia duration) and on development of prediction rules inclusive of individual factors to further refine the risk prediction. © The Author 2017. Published by Oxford University Press on behalf of The Journal of the Pediatric Infectious Diseases Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Daubenmier, Jennifer J; Weidner, Gerdi; Sumner, Michael D; Mendell, Nancy; Merritt-Worden, Terri; Studley, Joli; Ornish, Dean
2007-02-01
The relative contribution of health behaviors to coronary risk factors in multicomponent secondary coronary heart disease (CHD) prevention programs is largely unknown. Our purpose is to evaluate the additive and interactive effects of 3-month changes in health behaviors (dietary fat intake, exercise, and stress management) on 3-month changes in coronary risk and psychosocial factors among 869 nonsmoking CHD patients (34% female) enrolled in the health insurance-based Multisite Cardiac Lifestyle Intervention Program. Analyses of variance for repeated measures were used to analyze health behaviors, coronary risk factors, and psychosocial factors at baseline and 3 months. Multiple regression analyses evaluated changes in dietary fat intake and hours per week of exercise and stress management as predictors of changes in coronary risk and psychosocial factors. Significant overall improvement in coronary risk was observed. Reductions in dietary fat intake predicted reductions in weight, total cholesterol, low-density lipoprotein cholesterol, and interacted with increased exercise to predict reductions in perceived stress. Increases in exercise predicted improvements in total cholesterol and exercise capacity (for women). Increased stress management was related to reductions in weight, total cholesterol/high-density lipoprotein cholesterol (for men), triglycerides, hemoglobin A1c (in patients with diabetes), and hostility. Improvements in dietary fat intake, exercise, and stress management were individually, additively and interactively related to coronary risk and psychosocial factors, suggesting that multicomponent programs focusing on diet, exercise, and stress management may benefit patients with CHD.
Algorithms for the prediction of retinopathy of prematurity based on postnatal weight gain.
Binenbaum, Gil
2013-06-01
Current ROP screening guidelines represent a simple risk model with two dichotomized factors, birth weight and gestational age at birth. Pioneering work has shown that tracking postnatal weight gain, a surrogate for low insulin-like growth factor 1, may capture the influence of many other ROP risk factors and improve risk prediction. Models including weight gain, such as WINROP, ROPScore, and CHOP ROP, have demonstrated accurate ROP risk assessment and a potentially large reduction in ROP examinations, compared to current guidelines. However, there is a need for larger studies, and generalizability is limited in countries with developing neonatal care systems. Copyright © 2013 Elsevier Inc. All rights reserved.
Maizlin, Ilan I; Redden, David T; Beierle, Elizabeth A; Chen, Mike K; Russell, Robert T
2017-04-01
Surgical wound classification, introduced in 1964, stratifies the risk of surgical site infection (SSI) based on a clinical estimate of the inoculum of bacteria encountered during the procedure. Recent literature has questioned the accuracy of predicting SSI risk based on wound classification. We hypothesized that a more specific model founded on specific patient and perioperative factors would more accurately predict the risk of SSI. Using all observations from the 2012 to 2014 pediatric National Surgical Quality Improvement Program-Pediatric (NSQIP-P) Participant Use File, patients were randomized into model creation and model validation datasets. Potential perioperative predictive factors were assessed with univariate analysis for each of 4 outcomes: wound dehiscence, superficial wound infection, deep wound infection, and organ space infection. A multiple logistic regression model with a step-wise backwards elimination was performed. A receiver operating characteristic curve with c-statistic was generated to assess the model discrimination for each outcome. A total of 183,233 patients were included. All perioperative NSQIP factors were evaluated for clinical pertinence. Of the original 43 perioperative predictive factors selected, 6 to 9 predictors for each outcome were significantly associated with postoperative SSI. The predictive accuracy level of our model compared favorably with the traditional wound classification in each outcome of interest. The proposed model from NSQIP-P demonstrated a significantly improved predictive ability for postoperative SSIs than the current wound classification system. This model will allow providers to more effectively counsel families and patients of these risks, and more accurately reflect true risks for individual surgical patients to hospitals and payers. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
Edwards, Susan L.; Rapee, Ronald M.; Kennedy, Susan
2010-01-01
Background: Little is known about risk factors for anxiety in young children. The current study investigated the value of a set of theoretically derived risk factors to predict symptoms of anxiety in a sample of preschool-aged children. Methods: Mothers (n = 632) and fathers (n = 249) completed questionnaires twice, 12 months apart. Measures were…
Prediction of near-term breast cancer risk using a Bayesian belief network
NASA Astrophysics Data System (ADS)
Zheng, Bin; Ramalingam, Pandiyarajan; Hariharan, Harishwaran; Leader, Joseph K.; Gur, David
2013-03-01
Accurately predicting near-term breast cancer risk is an important prerequisite for establishing an optimal personalized breast cancer screening paradigm. In previous studies, we investigated and tested the feasibility of developing a unique near-term breast cancer risk prediction model based on a new risk factor associated with bilateral mammographic density asymmetry between the left and right breasts of a woman using a single feature. In this study we developed a multi-feature based Bayesian belief network (BBN) that combines bilateral mammographic density asymmetry with three other popular risk factors, namely (1) age, (2) family history, and (3) average breast density, to further increase the discriminatory power of our cancer risk model. A dataset involving "prior" negative mammography examinations of 348 women was used in the study. Among these women, 174 had breast cancer detected and verified in the next sequential screening examinations, and 174 remained negative (cancer-free). A BBN was applied to predict the risk of each woman having cancer detected six to 18 months later following the negative screening mammography. The prediction results were compared with those using single features. The prediction accuracy was significantly increased when using the BBN. The area under the ROC curve increased from an AUC=0.70 to 0.84 (p<0.01), while the positive predictive value (PPV) and negative predictive value (NPV) also increased from a PPV=0.61 to 0.78 and an NPV=0.65 to 0.75, respectively. This study demonstrates that a multi-feature based BBN can more accurately predict the near-term breast cancer risk than with a single feature.
Breast Cancer Risk Prediction and Mammography Biopsy Decisions
Armstrong, Katrina; Handorf, Elizabeth A.; Chen, Jinbo; Demeter, Mirar N. Bristol
2012-01-01
Background Controversy continues about screening mammography, in part because of the risk of false-negative and false-positive mammograms. Pre-test breast cancer risk factors may improve the positive and negative predictive value of screening. Purpose To create a model that estimates the potential impact of pre-test risk prediction using clinical and genomic information on the reclassification of women with abnormal mammograms (BI-RADS3 and BI-RADS4 [Breast Imaging-Reporting and Data System]) above and below the threshold for breast biopsy. Methods The current study modeled 1-year breast cancer risk in women with abnormal screening mammograms using existing data on breast cancer risk factors, 12 validated breast cancer single nucleotide polymorphisms (SNPs), and probability of cancer given the BI-RADS category. Examination was made of reclassification of women above and below biopsy thresholds of 1%, 2%, and 3% risk. The Breast Cancer Surveillance Consortium data were collected from 1996 to 2002. Data analysis was conducted in 2010 and 2011. Results Using a biopsy risk threshold of 2% and the standard risk factor model, 5% of women with a BI-RADS3 mammogram had a risk above the threshold, and 3% of women with BIRADS4A mammograms had a risk below the threshold. The addition of 12 SNPs in the model resulted in 8% of women with a BI-RADS3 mammogram above the threshold for biopsy and 7% of women with BI-RADS4A mammograms below the threshold. Conclusions The incorporation of pre-test breast cancer risk factors could change biopsy decisions for a small proportion of women with abnormal mammograms. The greatest impact comes from standard breast cancer risk factors. PMID:23253645
Nicoll, Rachel; Zhao, Ying; Ibrahimi, Pranvera; Olivecrona, Gunilla; Henein, Michael
2016-01-01
Background: The relationship of conventional cardiovascular risk factors (age, gender, ethnicity, diabetes, dyslipidaemia, hypertension, obesity, exercise, and the number of risk factors) to coronary artery calcification (CAC) presence and extent has never before been assessed in a systematic review and meta-analysis. Methods: We included only English language studies that assessed at least three conventional risk factors apart from age, gender, and ethnicity, but excluded studies in which all patients had another confirmed condition such as renal disease. Results: In total, 10 studies, comprising 15,769 patients, were investigated in the systematic review and seven studies, comprising 12,682 patients, were included in the meta-analysis, which demonstrated the importance of diabetes and hypertension as predictors of CAC presence and extent, with age also predicting CAC presence. Male gender, dyslipidaemia, family history of coronary artery disease, obesity, and smoking were overall not predictive of either CAC presence or extent, despite dyslipidaemia being a key risk factor for coronary artery disease (CAD). Conclusion: Diabetes and hypertension consistently predict the presence and extent of CAC in symptomatic patients. PMID:27608015
USDA-ARS?s Scientific Manuscript database
Objective: To examine the risk factors of developing functional decline and make probabilistic predictions by using a tree-based method that allows higher order polynomials and interactions of the risk factors. Methods: The conditional inference tree analysis, a data mining approach, was used to con...
Risk factors for invasive fungal disease in critically ill adult patients: a systematic review.
Muskett, Hannah; Shahin, Jason; Eyres, Gavin; Harvey, Sheila; Rowan, Kathy; Harrison, David
2011-01-01
Over 5,000 cases of invasive Candida species infections occur in the United Kingdom each year, and around 40% of these cases occur in critical care units. Invasive fungal disease (IFD) in critically ill patients is associated with increased morbidity and mortality at a cost to both the individual and the National Health Service. In this paper, we report the results of a systematic review performed to identify and summarise the important risk factors derived from published multivariable analyses, risk prediction models and clinical decision rules for IFD in critically ill adult patients to inform the primary data collection for the Fungal Infection Risk Evaluation Study. An internet search was performed to identify articles which investigated risk factors, risk prediction models or clinical decisions rules for IFD in critically ill adult patients. Eligible articles were identified in a staged process and were assessed by two investigators independently. The methodological quality of the reporting of the eligible articles was assessed using a set of questions addressing both general and statistical methodologies. Thirteen articles met the inclusion criteria, of which eight articles examined risk factors, four developed a risk prediction model or clinical decision rule and one evaluated a clinical decision rule. Studies varied in terms of objectives, risk factors, definitions and outcomes. The following risk factors were found in multiple studies to be significantly associated with IFD: surgery, total parenteral nutrition, fungal colonisation, renal replacement therapy, infection and/or sepsis, mechanical ventilation, diabetes, and Acute Physiology and Chronic Health Evaluation II (APACHE II) or APACHE III score. Several other risk factors were also found to be statistically significant in single studies only. Risk factor selection process and modelling strategy also varied across studies, and sample sizes were inadequate for obtaining reliable estimates. This review shows a number of risk factors to be significantly associated with the development of IFD in critically ill adults. Methodological limitations were identified in the design and conduct of studies in this area, and caution should be used in their interpretation.
Risk factors for invasive fungal disease in critically ill adult patients: a systematic review
2011-01-01
Introduction Over 5,000 cases of invasive Candida species infections occur in the United Kingdom each year, and around 40% of these cases occur in critical care units. Invasive fungal disease (IFD) in critically ill patients is associated with increased morbidity and mortality at a cost to both the individual and the National Health Service. In this paper, we report the results of a systematic review performed to identify and summarise the important risk factors derived from published multivariable analyses, risk prediction models and clinical decision rules for IFD in critically ill adult patients to inform the primary data collection for the Fungal Infection Risk Evaluation Study. Methods An internet search was performed to identify articles which investigated risk factors, risk prediction models or clinical decisions rules for IFD in critically ill adult patients. Eligible articles were identified in a staged process and were assessed by two investigators independently. The methodological quality of the reporting of the eligible articles was assessed using a set of questions addressing both general and statistical methodologies. Results Thirteen articles met the inclusion criteria, of which eight articles examined risk factors, four developed a risk prediction model or clinical decision rule and one evaluated a clinical decision rule. Studies varied in terms of objectives, risk factors, definitions and outcomes. The following risk factors were found in multiple studies to be significantly associated with IFD: surgery, total parenteral nutrition, fungal colonisation, renal replacement therapy, infection and/or sepsis, mechanical ventilation, diabetes, and Acute Physiology and Chronic Health Evaluation II (APACHE II) or APACHE III score. Several other risk factors were also found to be statistically significant in single studies only. Risk factor selection process and modelling strategy also varied across studies, and sample sizes were inadequate for obtaining reliable estimates. Conclusions This review shows a number of risk factors to be significantly associated with the development of IFD in critically ill adults. Methodological limitations were identified in the design and conduct of studies in this area, and caution should be used in their interpretation. PMID:22126425
Xiaoyong, Wu; Xuzhao, Li; Deliang, Yu; Pengfei, Yu; Zhenning, Hang; Bin, Bai; zhengyan, Li; Fangning, Pang; Shiqi, Wang; Qingchuan, Zhao
2017-01-01
Identifying patients at high risk of tube feeding intolerance (TFI) after gastric cancer surgery may prevent the occurrence of TFI; however, a predictive model is lacking. We therefore analyzed the incidence of TFI and its associated risk factors after gastric cancer surgery in 225 gastric cancer patients divided into without-TFI (n = 114) and with-TFI (n = 111) groups. A total of 49.3% of patients experienced TFI after gastric cancer. Multivariate analysis identified a history of functional constipation (FC), a preoperative American Society of Anesthesiologists (ASA) score of III, a high pain score at 6-hour postoperation, and a high white blood cell (WBC) count on the first day after surgery as independent risk factors for TFI. The area under the curve (AUC) was 0.756, with an optimal cut-off value of 0.5410. In order to identify patients at high risk of TFI after gastric cancer surgery, we constructed a predictive nomogram model based on the selected independent risk factors to indicate the probability of developing TFI. Use of our predictive nomogram model in screening, if a probability > 0.5410, indicated a high-risk patients would with a 70.1% likelihood of developing TFI. These high-risk individuals should take measures to prevent TFI before feeding with enteral nutrition. PMID:29245951
Knowledge of heart disease risk in a multicultural community sample of people with diabetes.
Wagner, Julie; Lacey, Kimberly; Abbott, Gina; de Groot, Mary; Chyun, Deborah
2006-06-01
Prevention of coronary heart disease (CHD) is a primary goal of diabetes management. Unfortunately, CHD risk knowledge is poor among people with diabetes. The objective is to determine predictors of CHD risk knowledge in a community sample of people with diabetes. A total of 678 people with diabetes completed the Heart Disease Facts Questionnaire (HDFQ), a valid and reliable measure of knowledge about the relationship between diabetes and heart disease. In regression analysis with demographics predicting HDFQ scores, sex, annual income, education, and health insurance status predicted HDFQ scores. In a separate regression analysis, having CHD risk factors did not predict HDFQ scores, however, taking medication for CHD risk factors did predict higher HDFQ scores. An analysis of variance showed significant differences between ethnic groups for HDFQ scores; Whites (M = 20.9) showed more CHD risk knowledge than African Americans (M = 19.6), who in turn showed more than Latinos (M = 18.2). Asians scored near Whites (M = 20.4) but did not differ significantly from any other group. Controlling for numerous demographic, socioeconomic, health care, diabetes, and cardiovascular health variables, the magnitude of ethnic differences was attenuated, but persisted. Education regarding modifiable risk factors must be delivered in a timely fashion so that lifestyle modification can be implemented and evaluated before pharmacotherapy is deemed necessary. African Americans and Latinos with diabetes are in the greatest need of education regarding CHD risk.
Assessing Risk Prediction Models Using Individual Participant Data From Multiple Studies
Pennells, Lisa; Kaptoge, Stephen; White, Ian R.; Thompson, Simon G.; Wood, Angela M.; Tipping, Robert W.; Folsom, Aaron R.; Couper, David J.; Ballantyne, Christie M.; Coresh, Josef; Goya Wannamethee, S.; Morris, Richard W.; Kiechl, Stefan; Willeit, Johann; Willeit, Peter; Schett, Georg; Ebrahim, Shah; Lawlor, Debbie A.; Yarnell, John W.; Gallacher, John; Cushman, Mary; Psaty, Bruce M.; Tracy, Russ; Tybjærg-Hansen, Anne; Price, Jackie F.; Lee, Amanda J.; McLachlan, Stela; Khaw, Kay-Tee; Wareham, Nicholas J.; Brenner, Hermann; Schöttker, Ben; Müller, Heiko; Jansson, Jan-Håkan; Wennberg, Patrik; Salomaa, Veikko; Harald, Kennet; Jousilahti, Pekka; Vartiainen, Erkki; Woodward, Mark; D'Agostino, Ralph B.; Bladbjerg, Else-Marie; Jørgensen, Torben; Kiyohara, Yutaka; Arima, Hisatomi; Doi, Yasufumi; Ninomiya, Toshiharu; Dekker, Jacqueline M.; Nijpels, Giel; Stehouwer, Coen D. A.; Kauhanen, Jussi; Salonen, Jukka T.; Meade, Tom W.; Cooper, Jackie A.; Cushman, Mary; Folsom, Aaron R.; Psaty, Bruce M.; Shea, Steven; Döring, Angela; Kuller, Lewis H.; Grandits, Greg; Gillum, Richard F.; Mussolino, Michael; Rimm, Eric B.; Hankinson, Sue E.; Manson, JoAnn E.; Pai, Jennifer K.; Kirkland, Susan; Shaffer, Jonathan A.; Shimbo, Daichi; Bakker, Stephan J. L.; Gansevoort, Ron T.; Hillege, Hans L.; Amouyel, Philippe; Arveiler, Dominique; Evans, Alun; Ferrières, Jean; Sattar, Naveed; Westendorp, Rudi G.; Buckley, Brendan M.; Cantin, Bernard; Lamarche, Benoît; Barrett-Connor, Elizabeth; Wingard, Deborah L.; Bettencourt, Richele; Gudnason, Vilmundur; Aspelund, Thor; Sigurdsson, Gunnar; Thorsson, Bolli; Kavousi, Maryam; Witteman, Jacqueline C.; Hofman, Albert; Franco, Oscar H.; Howard, Barbara V.; Zhang, Ying; Best, Lyle; Umans, Jason G.; Onat, Altan; Sundström, Johan; Michael Gaziano, J.; Stampfer, Meir; Ridker, Paul M.; Michael Gaziano, J.; Ridker, Paul M.; Marmot, Michael; Clarke, Robert; Collins, Rory; Fletcher, Astrid; Brunner, Eric; Shipley, Martin; Kivimäki, Mika; Ridker, Paul M.; Buring, Julie; Cook, Nancy; Ford, Ian; Shepherd, James; Cobbe, Stuart M.; Robertson, Michele; Walker, Matthew; Watson, Sarah; Alexander, Myriam; Butterworth, Adam S.; Angelantonio, Emanuele Di; Gao, Pei; Haycock, Philip; Kaptoge, Stephen; Pennells, Lisa; Thompson, Simon G.; Walker, Matthew; Watson, Sarah; White, Ian R.; Wood, Angela M.; Wormser, David; Danesh, John
2014-01-01
Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous. PMID:24366051
Assessing risk prediction models using individual participant data from multiple studies.
Pennells, Lisa; Kaptoge, Stephen; White, Ian R; Thompson, Simon G; Wood, Angela M
2014-03-01
Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous.
ERIC Educational Resources Information Center
McGaw, Sue; Scully, Tamara; Pritchard, Colin
2010-01-01
Objectives: This study set out to identify risk factors affecting parents with intellectual disabilities (IDs) by determining: (i) whether perception of family support differs between parents with IDs, referring professionals, and a specialist parenting service; (ii) whether multivariate familial and demographic factors differentiates "high-risk"…
IL-8 predicts pediatric oncology patients with febrile neutropenia at low risk for bacteremia.
Cost, Carrye R; Stegner, Martha M; Leonard, David; Leavey, Patrick
2013-04-01
Despite a low bacteremia rate, pediatric oncology patients are frequently admitted for febrile neutropenia. A pediatric risk prediction model with high sensitivity to identify patients at low risk for bacteremia is not available. We performed a single-institution prospective cohort study of pediatric oncology patients with febrile neutropenia to create a risk prediction model using clinical factors, respiratory viral infection, and cytokine expression. Pediatric oncology patients with febrile neutropenia were enrolled between March 30, 2010 and April 1, 2011 and managed per institutional protocol. Blood samples for C-reactive protein and cytokine expression and nasopharyngeal swabs for respiratory viral testing were obtained. Medical records were reviewed for clinical data. Statistical analysis utilized mixed multiple logistic regression modeling. During the 12-month period, 195 febrile neutropenia episodes were enrolled. There were 24 (12%) episodes of bacteremia. Univariate analysis revealed several factors predictive for bacteremia, and interleukin (IL)-8 was the most predictive variable in the multivariate stepwise logistic regression. Low serum IL-8 predicted patients at low risk for bacteremia with a sensitivity of 0.9 and negative predictive value of 0.98. IL-8 is a highly sensitive predictor for patients at low risk for bacteremia. IL-8 should be utilized in a multi-institution prospective trial to assign risk stratification to pediatric patients admitted with febrile neutropenia.
[Predictive factors of anxiety disorders].
Domschke, K
2014-10-01
Anxiety disorders are among the most frequent mental disorders in Europe (12-month prevalence 14%) and impose a high socioeconomic burden. The pathogenesis of anxiety disorders is complex with an interaction of biological, environmental and psychosocial factors contributing to the overall disease risk (diathesis-stress model). In this article, risk factors for anxiety disorders will be presented on several levels, e.g. genetic factors, environmental factors, gene-environment interactions, epigenetic mechanisms, neuronal networks ("brain fear circuit"), psychophysiological factors (e.g. startle response and CO2 sensitivity) and dimensional/subclinical phenotypes of anxiety (e.g. anxiety sensitivity and behavioral inhibition), and critically discussed regarding their potential predictive value. The identification of factors predictive of anxiety disorders will possibly allow for effective preventive measures or early treatment interventions, respectively, and reduce the individual patient's suffering as well as the overall socioeconomic burden of anxiety disorders.
Predicting stroke through genetic risk functions: The CHARGE risk score project
Ibrahim-Verbaas, Carla A; Fornage, Myriam; Bis, Joshua C; Choi, Seung Hoan; Psaty, Bruce M; Meigs, James B; Rao, Madhu; Nalls, Mike; Fontes, Joao D; O’Donnell, Christopher J.; Kathiresan, Sekar; Ehret, Georg B.; Fox, Caroline S; Malik, Rainer; Dichgans, Martin; Schmidt, Helena; Lahti, Jari; Heckbert, Susan R; Lumley, Thomas; Rice, Kenneth; Rotter, Jerome I; Taylor, Kent D; Folsom, Aaron R; Boerwinkle, Eric; Rosamond, Wayne D; Shahar, Eyal; Gottesman, Rebecca F.; Koudstaal, Peter J; Amin, Najaf; Wieberdink, Renske G.; Dehghan, Abbas; Hofman, Albert; Uitterlinden, André G; DeStefano, Anita L.; Debette, Stephanie; Xue, Luting; Beiser, Alexa; Wolf, Philip A.; DeCarli, Charles; Ikram, M. Arfan; Seshadri, Sudha; Mosley, Thomas H; Longstreth, WT; van Duijn, Cornelia M; Launer, Lenore J
2014-01-01
Background and Purpose Beyond the Framingham Stroke Risk Score (FSRS), prediction of future stroke may improve with a genetic risk score (GRS) based on Single nucleotide polymorphisms (SNPs) associated with stroke and its risk factors. Methods The study includes four population-based cohorts with 2,047 first incident strokes from 22,720 initially stroke-free European origin participants aged 55 years and older, who were followed for up to 20 years. GRS were constructed with 324 SNPs implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with Area under the curve (AUC) statistics comparing the GRS to age sex, and FSRS models, and with reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke (IS). Results In the meta-analysis, adding the GRS to the FSRS, age and sex model resulted in a significant improvement in discrimination (All stroke: Δjoint AUC =0.016, p-value=2.3*10-6; IS: Δ joint AUC =0.021, p-value=3.7*10−7), although the overall AUC remained low. In all studies there was a highly significantly improved net reclassification index (p-values <10−4). Conclusions The SNPs associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared to the classical epidemiological risk factors for stroke. PMID:24436238
Clyde, Merlise A.; Palmieri Weber, Rachel; Iversen, Edwin S.; Poole, Elizabeth M.; Doherty, Jennifer A.; Goodman, Marc T.; Ness, Roberta B.; Risch, Harvey A.; Rossing, Mary Anne; Terry, Kathryn L.; Wentzensen, Nicolas; Whittemore, Alice S.; Anton-Culver, Hoda; Bandera, Elisa V.; Berchuck, Andrew; Carney, Michael E.; Cramer, Daniel W.; Cunningham, Julie M.; Cushing-Haugen, Kara L.; Edwards, Robert P.; Fridley, Brooke L.; Goode, Ellen L.; Lurie, Galina; McGuire, Valerie; Modugno, Francesmary; Moysich, Kirsten B.; Olson, Sara H.; Pearce, Celeste Leigh; Pike, Malcolm C.; Rothstein, Joseph H.; Sellers, Thomas A.; Sieh, Weiva; Stram, Daniel; Thompson, Pamela J.; Vierkant, Robert A.; Wicklund, Kristine G.; Wu, Anna H.; Ziogas, Argyrios; Tworoger, Shelley S.; Schildkraut, Joellen M.
2016-01-01
Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted. PMID:27698005
Protective factors can mitigate behavior problems after prenatal cocaine and other drug exposures.
Bada, Henrietta S; Bann, Carla M; Whitaker, Toni M; Bauer, Charles R; Shankaran, Seetha; Lagasse, Linda; Lester, Barry M; Hammond, Jane; Higgins, Rosemary
2012-12-01
We determined the role of risk and protective factors on the trajectories of behavior problems associated with high prenatal cocaine exposure (PCE)/polydrug exposure. The Maternal Lifestyle Study enrolled 1388 children with or without PCE, assessed through age 15 years. Because most women using cocaine during pregnancy also used other substances, we analyzed for the effects of 4 categories of prenatal drug exposure: high PCE/other drugs (OD), some PCE/OD, OD/no PCE, and no PCE/no OD. Risks and protective factors at individual, family, and community levels that may be associated with behavior outcomes were entered stepwise into latent growth curve models, then replaced by cumulative risk and protective indexes, and finally by a combination of levels of risk and protective indexes. Main outcome measures were the trajectories of externalizing, internalizing, total behavior, and attention problems scores from the Child Behavior Checklist (parent). A total of 1022 (73.6%) children had known outcomes. High PCE/OD significantly predicted externalizing, total, and attention problems when considering the balance between risk and protective indexes. Some PCE/OD predicted externalizing and attention problems. OD/no PCE also predicted behavior outcomes except for internalizing behavior. High level of protective factors was associated with declining trajectories of problem behavior scores over time, independent of drug exposure and risk index scores. High PCE/OD is a significant risk for behavior problems in adolescence; protective factors may attenuate its detrimental effects. Clinical practice and public health policies should consider enhancing protective factors while minimizing risks to improve outcomes of drug-exposed children.
A Community-based Cross-sectional Study of Cardiovascular Risk in a Rural Community of Puducherry.
Shrivastava, Saurabh R; Ghorpade, Arun G; Shrivastava, Prateek S
2015-01-01
The World Health Organization (WHO) / International Society of Hypertension (ISH) risk prediction chart can predict the risk of cardiovascular events in any population. To assess the prevalence of cardiovascular risk factors and to estimate the cardiovascular risk using the WHO/ISH risk charts. A cross-sectional study was done from November 2011 to January 2012 in a rural area of Puducherry. Method of sampling was a single stage cluster random sampling, and subjects were enrolled depending on their suitability with the inclusion and exclusion criteria. The data collection tool was a piloted and semi-structured questionnaire, while WHO/ISH cardiovascular risk prediction charts for the South-East Asian region was used to predict the cardiovascular risk. Institutional Ethics committee permission was obtained before the start of the study. Statistical analysis was done using SPSS version 16 and appropriate statistical tests were applied. The mean age in years was 54.2 (±11.1) years with 46.7% of the participants being male. On application of the WHO/ISH risk prediction charts, almost 17% of the study subjects had moderate or high risk for a cardiovascular event. Additionally, high salt diet, alcohol use and low HDL levels, were identified as the major CVD risk factors. To conclude, stratification of people on the basis of risk prediction chart is a major step to have a clear idea about the magnitude of the problem. The findings of the current study revealed that there is a high burden of CVD risk in the rural Puducherry.
Glycated Hemoglobin Measurement and Prediction of Cardiovascular Disease
Angelantonio, Emanuele Di; Gao, Pei; Khan, Hassan; Butterworth, Adam S.; Wormser, David; Kaptoge, Stephen; Kondapally Seshasai, Sreenivasa Rao; Thompson, Alex; Sarwar, Nadeem; Willeit, Peter; Ridker, Paul M; Barr, Elizabeth L.M.; Khaw, Kay-Tee; Psaty, Bruce M.; Brenner, Hermann; Balkau, Beverley; Dekker, Jacqueline M.; Lawlor, Debbie A.; Daimon, Makoto; Willeit, Johann; Njølstad, Inger; Nissinen, Aulikki; Brunner, Eric J.; Kuller, Lewis H.; Price, Jackie F.; Sundström, Johan; Knuiman, Matthew W.; Feskens, Edith J. M.; Verschuren, W. M. M.; Wald, Nicholas; Bakker, Stephan J. L.; Whincup, Peter H.; Ford, Ian; Goldbourt, Uri; Gómez-de-la-Cámara, Agustín; Gallacher, John; Simons, Leon A.; Rosengren, Annika; Sutherland, Susan E.; Björkelund, Cecilia; Blazer, Dan G.; Wassertheil-Smoller, Sylvia; Onat, Altan; Marín Ibañez, Alejandro; Casiglia, Edoardo; Jukema, J. Wouter; Simpson, Lara M.; Giampaoli, Simona; Nordestgaard, Børge G.; Selmer, Randi; Wennberg, Patrik; Kauhanen, Jussi; Salonen, Jukka T.; Dankner, Rachel; Barrett-Connor, Elizabeth; Kavousi, Maryam; Gudnason, Vilmundur; Evans, Denis; Wallace, Robert B.; Cushman, Mary; D’Agostino, Ralph B.; Umans, Jason G.; Kiyohara, Yutaka; Nakagawa, Hidaeki; Sato, Shinichi; Gillum, Richard F.; Folsom, Aaron R.; van der Schouw, Yvonne T.; Moons, Karel G.; Griffin, Simon J.; Sattar, Naveed; Wareham, Nicholas J.; Selvin, Elizabeth; Thompson, Simon G.; Danesh, John
2015-01-01
IMPORTANCE The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. OBJECTIVE To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. DESIGN, SETTING, AND PARTICIPANTS Analysis of individual-participant data available from 73 prospective studies involving 294 998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. MAIN OUTCOMES AND MEASURES Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5%to <7.5%), and high (≥7.5%) risk. RESULTS During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20 840 incident fatal and nonfatal CVD outcomes (13 237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (−0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. CONCLUSIONS AND RELEVANCE In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk. PMID:24668104
Williams, Kirk R; Stansfield, Richard
2017-08-01
To manage intimate partner violence (IPV), the criminal justice system has turned to risk assessment instruments to predict if a perpetrator will reoffend. Empirically determining whether offenders assessed as high risk are those who recidivate is critical for establishing the predictive validity of IPV risk assessment instruments and for guiding the supervision of perpetrators. But by focusing solely on the relation between calculated risk scores and subsequent IPV recidivism, previous studies of the predictive validity of risk assessment instruments omitted mediating factors intended to mitigate the risk of this behavioral recidivism. The purpose of this study was to examine the mediating effects of such factors and the moderating effects of risk assessment on the relation between assessed risk (using the Domestic Violence Screening Instrument-Revised [DVSI-R]) and recidivistic IPV. Using a sample of 2,520 perpetrators of IPV, results revealed that time sentenced to jail and time sentenced to probation each significantly mediated the relation between DVSI-R risk level and frequency of reoffending. The results also revealed that assessed risk moderated the relation between these mediating factors and IPV recidivism, with reduced recidivism (negative estimated effects) for high-risk perpetrators but increased recidivism (positive estimate effects) for low-risk perpetrators. The implication is to assign interventions to the level of risk so that no harm is done. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Theobald, Delphine; Farrington, David P; Ttofi, Maria M; Crago, Rebecca V
2016-10-01
Dating violence is an important problem. Evidence suggests that women are more likely to perpetrate dating violence. The present study investigates the prevalence of dating violence compared with cohabiting violence in a community sample of men and women and assesses to what extent child and adolescent explanatory factors predict this behaviour. A secondary aim is to construct a risk score for dating violence based on the strongest risk factors. The Cambridge Study in Delinquent Development is a prospective longitudinal survey of 411 men (generation 2) born in the 1950s in an inner London area. Most recently, their sons and daughters [generation 3 (G3)] have been interviewed regarding their perpetration of dating and cohabiting violence, utilising the Conflict Tactics Scale. Risk factors were measured in four domains (family, parental, socio-economic and individual). A larger proportion of women than men perpetrated at least one act of violence towards their dating partner (36.4 vs 21.7%). There was a similar pattern for cohabiting violence (39.6 vs 21.4%). A number of risk factors were significantly associated with the perpetration of dating violence. For G3 women, these included a convicted father, parental conflict, large family size and poor housing. For G3 men, these included having a young father or mother, separation from the father before age 16, early school leaving, frequent truancy and having a criminal conviction. A risk score for both men and women, based on 10 risk factors, significantly predicted dating violence. Risk factors from four domains were important in predicting dating violence, but they were different for G3 men and women. It may be important to consider different risk factors and different risk assessments for male compared with female perpetration of dating violence. Early identification and interventions are recommended. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
A microRNA-based prediction model for lymph node metastasis in hepatocellular carcinoma.
Zhang, Li; Xiang, Zuo-Lin; Zeng, Zhao-Chong; Fan, Jia; Tang, Zhao-You; Zhao, Xiao-Mei
2016-01-19
We developed an efficient microRNA (miRNA) model that could predict the risk of lymph node metastasis (LNM) in hepatocellular carcinoma (HCC). We first evaluated a training cohort of 192 HCC patients after hepatectomy and found five LNM associated predictive factors: vascular invasion, Barcelona Clinic Liver Cancer stage, miR-145, miR-31, and miR-92a. The five statistically independent factors were used to develop a predictive model. The predictive value of the miRNA-based model was confirmed in a validation cohort of 209 consecutive HCC patients. The prediction model was scored for LNM risk from 0 to 8. The cutoff value 4 was used to distinguish high-risk and low-risk groups. The model sensitivity and specificity was 69.6 and 80.2%, respectively, during 5 years in the validation cohort. And the area under the curve (AUC) for the miRNA-based prognostic model was 0.860. The 5-year positive and negative predictive values of the model in the validation cohort were 30.3 and 95.5%, respectively. Cox regression analysis revealed that the LNM hazard ratio of the high-risk versus low-risk groups was 11.751 (95% CI, 5.110-27.021; P < 0.001) in the validation cohort. In conclusion, the miRNA-based model is reliable and accurate for the early prediction of LNM in patients with HCC.
Wang, Bo; Deveaux, Lynette; Li, Xiaoming; Marshall, Sharon; Chen, Xinguang; Stanton, Bonita
2014-04-01
Few studies have analyzed the development course beginning in pre-/early adolescence of overall engagement in health-risk behaviors and associated social risk factors that place individuals in different health-risk trajectories through mid-adolescence. The current longitudinal study identified 1276 adolescents in grade six and followed them for three years to investigate their developmental trajectories of risk behaviors and to examine the association of personal and social risk factors with each trajectory. Group-based trajectory modeling was applied to identify distinctive trajectory patterns of risk behaviors. Multivariate multinomial logistic regression analyses were performed to examine the effects of the personal and social risk factors on adolescents' trajectories. Three gender-specific behavioral trajectories were identified for males (55.3% low-risk, 37.6% moderate-risk, increasing, and 7.1% high-risk, increasing) and females (41.4% no-risk, 53.4% low-risk, increasing and 5.2% moderate to high-risk, increasing). Sensation-seeking, family, peer, and neighborhood factors at baseline predicted following the moderate-risk, increasing trajectory and the high-risk, increasing trajectory in males; these risk factors predicted following the moderate to high-risk, increasing trajectory in females. The presence of all three social risk factors (high-risk neighborhood, high-risk peers and low parental monitoring) had a dramatic impact on increased probability of being in a high-risk trajectory group. These findings highlight the developmental significance of early personal and social risk factors on subsequent risk behaviors in early to middle adolescence. Future adolescent health behavior promotion interventions might consider offering additional prevention resources to pre- and early adolescent youth who are exposed to multiple contextual risk factors (even in the absence of risk behaviors) or youth who are early-starters of delinquency and substance use behaviors in early adolescence. Copyright © 2014. Published by Elsevier Ltd.
Rhoades, Kimberly A; Leve, Leslie D; Eddy, J Mark; Chamberlain, Patricia
2016-12-01
Most juvenile offenders desist from offending as they become adults, but many continue and ultimately enter the adult corrections system. There has been little prospective examination of which variables may predict the latter transition, particularly for women. Our aim was to find out, for men and women separately, what variables identifiable in adolescent offenders predict their continuation of offending into adult life. Participants were 61 male and 81 female youths who had been referred from the juvenile justice system for chronic delinquency and recruited into randomised controlled trials comparing Multidimensional Treatment Foster Care with group care ('treatment as usual'). All participants had attained adulthood by the time of our study. We first examined gender differences in childhood risk factors and then used Cox proportional-hazards models to estimate the relationship of potential risk factors to first adult arrest. Results indicated that, for men, juvenile justice referrals alone predicted risk of any first adult arrest as well as arrest for felony arrest specifically. Each additional juvenile referral increased the risk of any adult arrest by 9% and of adult felony arrest by 8%. For women, family violence, parental divorce and cumulative childhood risk factors, but not juvenile justice referrals, were significant predictors of adult arrest. Each additional childhood risk factor increased the risk of adult arrest by 21%. Women who experienced parental divorce were nearly three times more likely to be arrested as an adult, and those who experienced family violence 2.5 times more so than those without such experiences. We found preliminary evidence of gender differences in childhood risk factors for adult offending, and, thus potentially, for the development and use of interventions tailored differently for girls and boys and young men and young women to reduce their risk of becoming adult recidivists. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
Geographic Profiling to Assess the Risk of Rare Plant Poaching in Natural Areas
NASA Astrophysics Data System (ADS)
Young, John A.; van Manen, Frank T.; Thatcher, Cindy A.
2011-09-01
We demonstrate the use of an expert-assisted spatial model to examine geographic factors influencing the poaching risk of a rare plant (American ginseng, Panax quinquefolius L.) in Shenandoah National Park, Virginia, USA. Following principles of the analytic hierarchy process (AHP), we identified a hierarchy of 11 geographic factors deemed important to poaching risk and requested law enforcement personnel of the National Park Service to rank those factors in a series of pair-wise comparisons. We used those comparisons to determine statistical weightings of each factor and combined them into a spatial model predicting poaching risk. We tested the model using 69 locations of previous poaching incidents recorded by law enforcement personnel. These locations occurred more frequently in areas predicted by the model to have a higher risk of poaching than random locations. The results of our study can be used to evaluate resource protection strategies and to target law enforcement activities.
Nielsen, Mette L; Pareek, Manan; Leósdóttir, Margrét; Eriksson, Karl-Fredrik; Nilsson, Peter M; Olsen, Michael H
2018-03-01
To examine the predictive capability of a 1-h vs 2-h postload glucose value for cardiovascular morbidity and mortality. Prospective, population-based cohort study (Malmö Preventive Project) with subject inclusion 1974-1992. 4934 men without known diabetes and cardiovascular disease, who had blood glucose (BG) measured at 0, 20, 40, 60, 90 and 120 min during an OGTT (30 g glucose per m 2 body surface area), were followed for 27 years. Data on cardiovascular events and death were obtained through national and local registries. Predictive capabilities of fasting BG (FBG) and glucose values obtained during OGTT alone and added to a clinical prediction model comprising traditional cardiovascular risk factors were assessed using Harrell's concordance index (C-index) and integrated discrimination improvement (IDI). Median age was 48 (25th-75th percentile: 48-49) years and mean FBG 4.6 ± 0.6 mmol/L. FBG and 2-h postload BG did not independently predict cardiovascular events or death. Conversely, 1-h postload BG predicted cardiovascular morbidity and mortality and remained an independent predictor of cardiovascular death (HR: 1.09, 95% CI: 1.01-1.17, P = 0.02) and all-cause mortality (HR: 1.10, 95% CI: 1.05-1.16, P < 0.0001) after adjusting for various traditional risk factors. Clinical risk factors with added 1-h postload BG performed better than clinical risk factors alone, in predicting cardiovascular death (likelihood-ratio test, P = 0.02) and all-cause mortality (likelihood-ratio test, P = 0.0001; significant IDI, P = 0.0003). Among men without known diabetes, addition of 1-h BG, but not FBG or 2-h BG, to clinical risk factors provided incremental prognostic yield for prediction of cardiovascular death and all-cause mortality. © 2018 European Society of Endocrinology.
Cho, In-Jeong; Sung, Ji Min; Chang, Hyuk-Jae; Chung, Namsik; Kim, Hyeon Chang
2017-11-01
Increasing evidence suggests that repeatedly measured cardiovascular disease (CVD) risk factors may have an additive predictive value compared with single measured levels. Thus, we evaluated the incremental predictive value of incorporating periodic health screening data for CVD prediction in a large nationwide cohort with periodic health screening tests. A total of 467 708 persons aged 40 to 79 years and free from CVD were randomly divided into development (70%) and validation subcohorts (30%). We developed 3 different CVD prediction models: a single measure model using single time point screening data; a longitudinal average model using average risk factor values from periodic screening data; and a longitudinal summary model using average values and the variability of risk factors. The development subcohort included 327 396 persons who had 3.2 health screenings on average and 25 765 cases of CVD over 12 years. The C statistics (95% confidence interval [CI]) for the single measure, longitudinal average, and longitudinal summary models were 0.690 (95% CI, 0.682-0.698), 0.695 (95% CI, 0.687-0.703), and 0.752 (95% CI, 0.744-0.760) in men and 0.732 (95% CI, 0.722-0.742), 0.735 (95% CI, 0.725-0.745), and 0.790 (95% CI, 0.780-0.800) in women, respectively. The net reclassification index from the single measure model to the longitudinal average model was 1.78% in men and 1.33% in women, and the index from the longitudinal average model to the longitudinal summary model was 32.71% in men and 34.98% in women. Using averages of repeatedly measured risk factor values modestly improves CVD predictability compared with single measurement values. Incorporating the average and variability information of repeated measurements can lead to great improvements in disease prediction. URL: https://www.clinicaltrials.gov. Unique identifier: NCT02931500. © 2017 American Heart Association, Inc.
A multiple biomarker risk score for guiding clinical decisions using a decision curve approach.
Hughes, Maria F; Saarela, Olli; Blankenberg, Stefan; Zeller, Tanja; Havulinna, Aki S; Kuulasmaa, Kari; Yarnell, John; Schnabel, Renate B; Tiret, Laurence; Salomaa, Veikko; Evans, Alun; Kee, Frank
2012-08-01
We assessed whether a cardiovascular risk model based on classic risk factors (e.g. cholesterol, blood pressure) could refine disease prediction if it included novel biomarkers (C-reactive protein, N-terminal pro-B-type natriuretic peptide, troponin I) using a decision curve approach which can incorporate clinical consequences. We evaluated whether a model including biomarkers and classic risk factors could improve prediction of 10 year risk of cardiovascular disease (CVD; chronic heart disease and ischaemic stroke) against a classic risk factor model using a decision curve approach in two prospective MORGAM cohorts. This included 7739 men and women with 457 CVD cases from the FINRISK97 cohort; and 2524 men with 259 CVD cases from PRIME Belfast. The biomarker model improved disease prediction in FINRISK across the high-risk group (20-40%) but not in the intermediate risk group, at the 23% risk threshold net benefit was 0.0033 (95% CI 0.0013-0.0052). However, in PRIME Belfast the net benefit of decisions guided by the decision curve was improved across intermediate risk thresholds (10-20%). At p(t) = 10% in PRIME, the net benefit was 0.0059 (95% CI 0.0007-0.0112) with a net increase in 6 true positive cases per 1000 people screened and net decrease of 53 false positive cases per 1000 potentially leading to 5% fewer treatments in patients not destined for an event. The biomarker model improves 10-year CVD prediction at intermediate and high-risk thresholds and in particular, could be clinically useful at advising middle-aged European males of their CVD risk.
Child-related cognitions and affective functioning of physically abusive and comparison parents.
Haskett, Mary E; Smith Scott, Susan; Grant, Raven; Ward, Caryn Sabourin; Robinson, Canby
2003-06-01
The goal of this research was to utilize the cognitive behavioral model of abusive parenting to select and examine risk factors to illuminate the unique and combined influences of social cognitive and affective variables in predicting abuse group membership. Participants included physically abusive parents (n=56) and a closely-matched group of comparison parents (n=62). Social cognitive risk variables measured were (a) parent's expectations for children's abilities and maturity, (b) parental attributions of intentionality of child misbehavior, and (c) parents' perceptions of their children's adjustment. Affective risk variables included (a) psychopathology and (b) parenting stress. A series of logistic regression models were constructed to test the individual, combined, and interactive effects of risk variables on abuse group membership. The full set of five risk variables was predictive of abuse status; however, not all variables were predictive when considered individually and interactions did not contribute significantly to prediction. A risk composite score computed for each parent based on the five risk variables significantly predicted abuse status. Wide individual differences in risk across the five variables were apparent within the sample of abusive parents. Findings were generally consistent with a cognitive behavioral model of abuse, with cognitive variables being more salient in predicting abuse status than affective factors. Results point to the importance of considering diversity in characteristics of abusive parents.
The predictive role of health-promoting behaviours and perceived stress in aneurysmal rupture.
Lee, Mi-Sun; Park, Chang G; Hughes, Tonda L; Jun, Sang-Eun; Whang, Kum; Kim, Nahyun
2018-03-01
To examine the roles of two modifiable factors-health-promoting behaviours and perceived stress-in predicting aneurysmal rupture. Unruptured intracranial aneurysm detection produces significant stress and anxiety in patients because of the risk of rupture. Compared to nonmodifiable risk factors for rupture such as age, gender and aneurysm size/location, less attention has been given to modifiable risk factors. Two modifiable factors, health-promoting behaviours and perceived stress, have hardly been examined as potential predictors of rupture. This study used a cross-sectional design. We assessed 155 patients with intracranial aneurysms-that is, subarachnoid haemorrhage (n = 77) or unruptured intracranial aneurysm (n = 78)-to examine (i) baseline characteristics (patient and aneurysmal factors), (ii) health-related factors (lifestyle habits and health-promoting behaviour) and (iii) perceived stress levels (psychological stress and physical stress). Patient records provided medical histories and aneurysmal factors; other data were collected using a structured questionnaire addressing lifestyle habits, the Health-Promoting Lifestyle Profile-II to measure health-promoting behaviour and the Perceived Stress Questionnaire to measure perceived-psychological stress and perceived-physical stress levels. Bivariate analysis indicated that aneurysm rupture risk was associated with female gender, aneurysm size/location, defecation frequency, hyperlipidaemia, sedentary time, low Health-Promoting Lifestyle Profile-II mean scores and high perceived-psychological stress scores. After adjusting for known risk factors, the mean Health-Promoting Lifestyle Profile-II and perceived-psychological stress scores remained robust predictors of rupture. Furthermore, known risk factors combined with these scores had greater predictive power than known risk factors alone. Health-promoting behaviour and psychological stress are promising modifiable factors for reducing risk of aneurysmal rupture. Our findings may stimulate greater understanding of mechanisms underlying aneurysmal rupture and suggest practical strategies for nurses to employ in optimising conservative management of rupture risk by teaching patients how to modify their risk. Both health-promoting behaviour and perceived stress should be addressed when designing preventive nursing interventions for patients with unruptured intracranial aneurysm. © 2017 John Wiley & Sons Ltd.
Personal and couple level risk factors: Maternal and paternal parent-child aggression risk.
Tucker, Meagan C; Rodriguez, Christina M; Baker, Levi R
2017-07-01
Previous literature examining parent-child aggression (PCA) risk has relied heavily upon mothers, limiting our understanding of paternal risk factors. Moreover, the extent to which factors in the couple relationship work in tandem with personal vulnerabilities to impact PCA risk is unclear. The current study examined whether personal stress and distress predicted PCA risk (child abuse potential, over-reactive discipline style, harsh discipline practices) for fathers as well as mothers and whether couple functioning mediated versus moderated the relation between personal stress and PCA risk in a sample of 81 couples. Additionally, the potential for risk factors in one partner to cross over and affect their partner's PCA risk was considered. Findings indicated higher personal stress predicted elevated maternal and paternal PCA risk. Better couple functioning did not moderate this relationship but partially mediated stress and PCA risk for both mothers and fathers. In addition, maternal stress evidenced a cross-over effect, wherein mothers' personal stress linked to fathers' couple functioning. Findings support the role of stress and couple functioning in maternal and paternal PCA risk, including potential cross-over effects that warrant further inquiry. Copyright © 2017 Elsevier Ltd. All rights reserved.
Mbeutcha, Aurélie; Mathieu, Romain; Rouprêt, Morgan; Gust, Kilian M; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F
2016-10-01
In the context of customized patient care for upper tract urothelial carcinoma (UTUC), decision-making could be facilitated by risk assessment and prediction tools. The aim of this study was to provide a critical overview of existing predictive models and to review emerging promising prognostic factors for UTUC. A literature search of articles published in English from January 2000 to June 2016 was performed using PubMed. Studies on risk group stratification models and predictive tools in UTUC were selected, together with studies on predictive factors and biomarkers associated with advanced-stage UTUC and oncological outcomes after surgery. Various predictive tools have been described for advanced-stage UTUC assessment, disease recurrence and cancer-specific survival (CSS). Most of these models are based on well-established prognostic factors such as tumor stage, grade and lymph node (LN) metastasis, but some also integrate newly described prognostic factors and biomarkers. These new prediction tools seem to reach a high level of accuracy, but they lack external validation and decision-making analysis. The combinations of patient-, pathology- and surgery-related factors together with novel biomarkers have led to promising predictive tools for oncological outcomes in UTUC. However, external validation of these predictive models is a prerequisite before their introduction into daily practice. New models predicting response to therapy are urgently needed to allow accurate and safe individualized management in this heterogeneous disease.
Variance computations for functional of absolute risk estimates.
Pfeiffer, R M; Petracci, E
2011-07-01
We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.
Variance computations for functional of absolute risk estimates
Pfeiffer, R.M.; Petracci, E.
2011-01-01
We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates. PMID:21643476
Prognostic importance of DNA ploidy in non-endometrioid, high-risk endometrial carcinomas.
Sorbe, Bengt
2016-03-01
The present study investigated the predictive and prognostic impact of DNA ploidy together with other well-known prognostic factors in a series of non-endometrioid, high-risk endometrial carcinomas. From a complete consecutive series of 4,543 endometrial carcinomas of International Federation of Gynecology and Obstetrics (FIGO) stages I-IV, 94 serous carcinomas, 48 clear cell carcinomas and 231 carcinosarcomas were selected as a non-endometrioid, high-risk group for further studies regarding prognosis. The impact of DNA ploidy, as assessed by flow cytometry, was of particular focus. The age of the patients, FIGO stage, depth of myometrial infiltration and tumor expression of p53 were also included in the analyses (univariate and multivariate). In the complete series of cases, the recurrence rate was 37%, and the 5-year overall survival rate was 39% with no difference between the three histological subtypes. The primary cure rate (78%) was also similar for all tumor types studied. DNA ploidy was a significant predictive factor (on univariate analysis) for primary tumor cure rate, and a prognostic factor for survival rate (on univariate and multivariate analyses). The predictive and prognostic impact of DNA ploidy was higher in carcinosarcomas than in serous and clear cell carcinomas. In the majority of multivariate analyses, FIGO stage and depth of myometrial infiltration were the most important predictive (tumor recurrence) and prognostic (survival rate) factors. DNA ploidy status is a less important predictive and prognostic factor in non-endometrioid, high-risk endometrial carcinomas than in the common endometrioid carcinomas, in which FIGO and nuclear grade also are highly significant and important factors.
Monsuur, Alienke J; de Bakker, Paul I W; Zhernakova, Alexandra; Pinto, Dalila; Verduijn, Willem; Romanos, Jihane; Auricchio, Renata; Lopez, Ana; van Heel, David A; Crusius, J Bart A; Wijmenga, Cisca
2008-05-28
The HLA genes, located in the MHC region on chromosome 6p21.3, play an important role in many autoimmune disorders, such as celiac disease (CD), type 1 diabetes (T1D), rheumatoid arthritis, multiple sclerosis, psoriasis and others. Known HLA variants that confer risk to CD, for example, include DQA1*05/DQB1*02 (DQ2.5) and DQA1*03/DQB1*0302 (DQ8). To diagnose the majority of CD patients and to study disease susceptibility and progression, typing these strongly associated HLA risk factors is of utmost importance. However, current genotyping methods for HLA risk factors involve many reactions, and are complicated and expensive. We sought a simple experimental approach using tagging SNPs that predict the CD-associated HLA risk factors. Our tagging approach exploits linkage disequilibrium between single nucleotide polymorphism (SNPs) and the CD-associated HLA risk factors DQ2.5 and DQ8 that indicate direct risk, and DQA1*0201/DQB1*0202 (DQ2.2) and DQA1*0505/DQB1*0301 (DQ7) that attribute to the risk of DQ2.5 to CD. To evaluate the predictive power of this approach, we performed an empirical comparison of the predicted DQ types, based on these six tag SNPs, with those executed with current validated laboratory typing methods of the HLA-DQA1 and -DQB1 genes in three large cohorts. The results were validated in three European celiac populations. Using this method, only six SNPs were needed to predict the risk types carried by >95% of CD patients. We determined that for this tagging approach the sensitivity was >0.991, specificity >0.996 and the predictive value >0.948. Our results show that this tag SNP method is very accurate and provides an excellent basis for population screening for CD. This method is broadly applicable in European populations.
ERIC Educational Resources Information Center
Roskam, I.; Meunier, J.-C.; Stievenart, M.; Noel, M.-P.
2013-01-01
The main objective of the current study was to examine the impact of two child risk factors, i.e. personality and inhibition, and two proximal family risk factors, i.e. parenting and attachment, and the impact of their cumulative effect on later externalizing behavior among young children incurring no distal family risk. Data were collected in a…
Multifactorial disease risk calculator: Risk prediction for multifactorial disease pedigrees.
Campbell, Desmond D; Li, Yiming; Sham, Pak C
2018-03-01
Construction of multifactorial disease models from epidemiological findings and their application to disease pedigrees for risk prediction is nontrivial for all but the simplest of cases. Multifactorial Disease Risk Calculator is a web tool facilitating this. It provides a user-friendly interface, extending a reported methodology based on a liability-threshold model. Multifactorial disease models incorporating all the following features in combination are handled: quantitative risk factors (including polygenic scores), categorical risk factors (including major genetic risk loci), stratified age of onset curves, and the partition of the population variance in disease liability into genetic, shared, and unique environment effects. It allows the application of such models to disease pedigrees. Pedigree-related outputs are (i) individual disease risk for pedigree members, (ii) n year risk for unaffected pedigree members, and (iii) the disease pedigree's joint liability distribution. Risk prediction for each pedigree member is based on using the constructed disease model to appropriately weigh evidence on disease risk available from personal attributes and family history. Evidence is used to construct the disease pedigree's joint liability distribution. From this, lifetime and n year risk can be predicted. Example disease models and pedigrees are provided at the website and are used in accompanying tutorials to illustrate the features available. The website is built on an R package which provides the functionality for pedigree validation, disease model construction, and risk prediction. Website: http://grass.cgs.hku.hk:3838/mdrc/current. © 2017 WILEY PERIODICALS, INC.
Borges, Guilherme; Nock, Matthew K.; Haro Abad, Josep M.; Hwang, Irving; Sampson, Nancy A.; Alonso, Jordi; Andrade, Laura Helena; Angermeyer, Matthias C.; Beautrais, Annette; Bromet, Evelyn; Bruffaerts, Ronny; de Girolamo, Giovanni; Florescu, Silvia; Gureje, Oye; Hu, Chiyi; Karam, Elie G; Kovess-Masfety, Viviane; Lee, Sing; Levinson, Daphna; Medina-Mora, Maria Elena; Ormel, Johan; Posada-Villa, Jose; Sagar, Rajesh; Tomov, Toma; Uda, Hidenori; Williams, David R.; Kessler, Ronald C.
2009-01-01
Objective Although suicide is a leading cause of death worldwide, clinicians and researchers lack a data-driven method to assess the risk of suicide attempts. This study reports the results of an analysis of a large cross-national epidemiological survey database that estimates the 12-month prevalence of suicidal behaviors, identifies risk factors for suicide attempts, and combines these factors to create a risk index for 12-month suicide attempts separately for developed and developing countries. Method Data come from the WHO World Mental Health (WMH) Surveys (conducted 2001–2007) in which 108,705 adults from 21 countries were interviewed using the WHO Composite International Diagnostic Interview (CIDI). The survey assessed suicidal behaviors and potential risk factors across multiple domains including: socio-demographics, parent psychopathology, childhood adversities, DSM-IV disorders, and history of suicidal behavior. Results Twelve-month prevalence estimates of suicide ideation, plans and attempts are 2.0%, 0.6% and 0.3% respectively for developed countries and 2.1%, 0.7% and 0.4% for developing countries. Risk factors for suicidal behaviors in both developed and developing countries include: female sex, younger age, lower education and income, unmarried status, unemployment, parent psychopathology, childhood adversities, and presence of diverse 12-month DSM-IV mental disorders. Combining risk factors from multiple domains produced risk indices that accurately predicted 12-month suicide attempts in both developed and developing countries (AUC=.74–.80). Conclusion Suicidal behaviors occur at similar rates in both developed and developing countries. Risk indices assessing multiple domains can predict suicide attempts with fairly good accuracy and may be useful in aiding clinicians in the prediction of these behaviors. PMID:20816034
NASA Astrophysics Data System (ADS)
Blauhut, Veit; Stahl, Kerstin; Stagge, James Howard; Tallaksen, Lena M.; De Stefano, Lucia; Vogt, Jürgen
2016-07-01
Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, meant as the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work tests the capability of commonly applied drought indices and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and combines information on past drought impacts, drought indices, and vulnerability factors into estimates of drought risk at the pan-European scale. This hybrid approach bridges the gap between traditional vulnerability assessment and probabilistic impact prediction in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro-region-specific sensitivities of drought indices, with the Standardized Precipitation Evapotranspiration Index (SPEI) for a 12-month accumulation period as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictors, with information about land use and water resources being the best vulnerability-based predictors. The application of the hybrid approach revealed strong regional and sector-specific differences in drought risk across Europe. The majority of the best predictor combinations rely on a combination of SPEI for shorter and longer accumulation periods, and a combination of information on land use and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, appropriateness of drought indices selection for specific applications, and drought risk assessment.
[From "deadly quartet" to "metabolic syndrome". An analysis of its clinical relevance].
Vancheri, Federico; Burgio, Antonio; Dovico, Rossana
2007-03-01
The metabolic syndrome denotes a clustering of specific risk factors for both cardiovascular disease and type 2 diabetes, whose underlying pathophysiology is believed to include insulin resistance. It has been widely reported that the syndrome is a simple clinical tool to identify people at high long term risk of cardiovascular disease and diabetes. However, its clinical importance is under debate. There are substantial uncertainties about the clinical definition of the syndrome, as to whether the risk factors clustering indicates a single unifying disorder, whether the risk conferred by the condition as a whole is higher risk than its individual components, and whether its predictive value of future cardiovascular events or diabetes is greater than established predicting models such as the Framingham Risk Score and the Diabetes Risk Score. We undertook an extensive review of the literature. Our analysis indicates that current definitions of the syndrome are incomplete or ambiguous, more than one pathophysiological process underlies the syndrome, although the combination of insulin resistance and hyperinsulinemia are related to most cases; the risk associated with the syndrome is no greater than that explained by the presence of its components, and the syndrome is less effective in predicting the future development of cardiovascular events and diabetes than established predicting models. Although the syndrome has some importance in understanding the pathophysiology of cardiovascular and diabetes risk factors clustering, its use as a clinical syndrome is not justified by current data.
Tomaselli Muensterman, Elena; Tisdale, James E
2018-06-08
Prolongation of the heart rate-corrected QT (QTc) interval increases the risk for torsades de pointes (TdP), a potentially fatal arrhythmia. The likelihood of TdP is higher in patients with risk factors, which include female sex, older age, heart failure with reduced ejection fraction, hypokalemia, hypomagnesemia, concomitant administration of ≥ 2 QTc interval-prolonging medications, among others. Assessment and quantification of risk factors may facilitate prediction of patients at highest risk for developing QTc interval prolongation and TdP. Investigators have utilized the field of predictive analytics, which generates predictions using techniques including data mining, modeling, machine learning, and others, to develop methods of risk quantification and prediction of QTc interval prolongation. Predictive analytics have also been incorporated into clinical decision support (CDS) tools to alert clinicians regarding patients at increased risk of developing QTc interval prolongation. The objectives of this paper are to assess the effectiveness of predictive analytics for identification of patients at risk of drug-induced QTc interval prolongation, and to discuss the efficacy of incorporation of predictive analytics into CDS tools in clinical practice. A systematic review of English language articles (human subjects only) was performed, yielding 57 articles, with an additional 4 articles identified from other sources; a total of 10 articles were included in this review. Risk scores for QTc interval prolongation have been developed in various patient populations including those in cardiac intensive care units (ICUs) and in broader populations of hospitalized or health system patients. One group developed a risk score that includes information regarding genetic polymorphisms; this score significantly predicted TdP. Development of QTc interval prolongation risk prediction models and incorporation of these models into CDS tools reduces the risk of QTc interval prolongation in cardiac ICUs and identifies health-system patients at increased risk for mortality. The impact of these QTc interval prolongation predictive analytics on overall patient safety outcomes, such as TdP and sudden cardiac death relative to the cost of development and implementation, requires further study. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Shoulder dystocia: prediction and management.
Hill, Meghan G; Cohen, Wayne R
2016-01-01
Shoulder dystocia is a complication of vaginal delivery and the primary factor associated with brachial plexus injury. In this review, we discuss the risk factors for shoulder dystocia and propose a framework for the prediction and prevention of the complication. A recommended approach to management when shoulder dystocia occurs is outlined, with review of the maneuvers used to relieve the obstruction with minimal risk of fetal and maternal injury.
ERIC Educational Resources Information Center
Peters, S. Colby; Woolley, Michael E.
2015-01-01
Data from the School Success Profile generated by 19,228 middle and high school students were organized into three broad categories of risk and protective factors--control, support, and challenge--to examine the relative and combined power of aggregate scale scores in each category so as to predict academic success. It was hypothesized that higher…
Determinants of sick-leave duration: a tool for managers?
Flach, Peter A; Krol, Boudien; Groothoff, Johan W
2008-09-01
To provide managers with tools to manage episodes of sick-leave of their employees, the influence of factors such as age, gender, duration of tenure, working full-time or part-time, cause and history of sick-leave, salary and education on sick-leave duration was studied. In a cross-sectional study, data derived from the 2005 sick-leave files of a Dutch university were examined. Odds ratios of the single risk factors were calculated for short spells (
ERIC Educational Resources Information Center
Friedman, Alfred S.; And Others
1995-01-01
Gathered substance use histories from African American male (n=318) and female (n=322) adolescents to determine whether gender differences affected early life risk factors for drug use or abuse. Family variables and subject behavior predicted degree of substance use and frequency of intoxication, but no risk factor applied to both genders. (SNR)
Protective Factors Against Depression and Suicidal Behaviour in Adolescence
Breton, Jean-Jacques; Labelle, Réal; Berthiaume, Claude; Royer, Chantal; St-Georges, Marie; Ricard, Dominique; Abadie, Pascale; Gérardin, Priscille; Cohen, David; Guilé, Jean-Marc
2015-01-01
Objectives: To examine whether protective factors in the Protection for Adolescent Depression Study (PADS) moderate the impact of stressful events on depression and suicidal behaviour in the community and a clinical setting; and to study the influence of sex. Method: Participants were 283 adolescents from the community and 119 from a mood disorder clinic in Montreal. The participants were evaluated on 6 instruments measuring individual risk and protective factors. Descriptive analyses and univariate and multiple logistic regression models were carried out. Results: Risk factors predicted higher levels of depression and presence of suicidal behaviour, and protective factors predicted lower levels of depression and absence of suicidal behaviour, as expected under the vulnerability-resilience stress model. Several sex differences were observed in terms of the predictive power of risk factors (for example, hopelessness among girls and keep to themselves among boys) and protective factors (for example, focusing on the positive among girls and self-discovery among boys). Conclusions: Findings from the PADS suggest that protective factors moderate the impact of stress on depression and suicidal behaviour. Developing protection appears important in the presence of chronic conditions, such as depressive disorders, to reduce the likelihood of further episodes. The influence of sex makes it all the more relevant to target different factors for boys and girls to increase protection and decrease risk in prevention and intervention programs. PMID:25886672
Wu, Yazhou; Zhang, Ling; Yuan, Xiaoyan; Wu, Yamin; Yi, Dong
2011-04-01
The objective of this study is to investigate the risk factors of stroke in a community in Chongqing by setting quantitative criteria for determining the risk factors of stroke. Thus, high-risk individuals can be identified and laid a foundation for predicting individual risk of stroke. 1,034 cases with 1:2 matched controls (2,068) were chosen from five communities in Chongqing including Shapingba, Xiaolongkan, Tianxingqiao, Yubei Road and Ciqikou. Participants were interviewed with a uniform questionnaire. The risk factors of stroke and the odds ratios of risk factors were analyzed with a logistic regression model, and risk exposure factors of different levels were converted into risk scores using statistical models. For men, ten risk factors including hypertension (5.728), family history of stroke (4.599), and coronary heart disease (5.404), among others, were entered into the main effect model. For women, 11 risk factors included hypertension (5.270), family history of stroke (4.866), hyperlipidemia (4.346), among others. The related risk scores were added to obtain a combined risk score to predict the individual's risk of stoke in the future. An individual health risk appraisal model of stroke, which was applicable to individuals of different gender, age, health behavior, disease and family history, was established. In conclusion, personal diseases including hypertension, diabetes mellitus, etc., were very important to the prevalence of stoke. The prevalence of stroke can be effectively reduced by changing unhealthy lifestyles and curing the positive individual disease. The study lays a foundation for health education to persuade people to change their unhealthy lifestyles or behaviors, and could be used in community health services.
Gene Expression Profiling Predicts the Development of Oral Cancer
Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li
2011-01-01
Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635
Williams, Tricia S; Connolly, Jennifer; Pepler, Debra; Craig, Wendy; Laporte, Lise
2008-08-01
The present study examined physical dating aggression in different adolescent relationships and assessed linear, threshold, and moderator risk models for recurrent aggressive relationships. The 621 participants (59% girls, 41% boys) were drawn from a 1-year longitudinal survey of Canadian high school youths ranging from Grade 9 through Grade 12. Approximately 13% of participants reported recurrent dating aggression across 2 different relationships. Using peer and dyadic risk factors from Time 1 of the study, the authors confirmed a linear risk model, such that adolescents in 2 different violent relationships had significantly more contextual risk factors than did adolescents in 1 or no violent relationship. Further, structural equation modeling assessing moderation of contextual risk factors indicated that, for adolescents with high acceptance of dating aggression, peer aggression and delinquency significantly predicted recurrent aggression in a new relationship. In comparison, for adolescents with low acceptance of dating aggression, negative relationship characteristics significantly predicted recurrent aggression. Acceptance did not moderate concurrent associations between risk factors and aggression in 1 relationship. Results support a developmental psychopathological approach to the understanding of recurrent aggression and its associated risk factors. Copyright 2008 APA, all rights reserved.
King, Michael; Marston, Louise; Švab, Igor; Maaroos, Heidi-Ingrid; Geerlings, Mirjam I.; Xavier, Miguel; Benjamin, Vicente; Torres-Gonzalez, Francisco; Bellon-Saameno, Juan Angel; Rotar, Danica; Aluoja, Anu; Saldivia, Sandra; Correa, Bernardo; Nazareth, Irwin
2011-01-01
Background Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. Methods A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women. Results 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). Conclusions The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse. PMID:21853028
King, Michael; Marston, Louise; Švab, Igor; Maaroos, Heidi-Ingrid; Geerlings, Mirjam I; Xavier, Miguel; Benjamin, Vicente; Torres-Gonzalez, Francisco; Bellon-Saameno, Juan Angel; Rotar, Danica; Aluoja, Anu; Saldivia, Sandra; Correa, Bernardo; Nazareth, Irwin
2011-01-01
Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women. 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.
Desmarais, Sarah L.; Nicholls, Tonia L.; Wilson, Catherine M.; Brink, Johann
2012-01-01
The Short-Term Assessment of Risk and Treatability (START) is a relatively new structured professional judgment guide for the assessment and management of short-term risks associated with mental, substance use, and personality disorders. The scheme may be distinguished from other violence risk instruments because of its inclusion of 20 dynamic factors that are rated in terms of both vulnerability and strength. This study examined the reliability and validity of START assessments in predicting inpatient aggression. Research assistants completed START assessments for 120 male forensic psychiatric patients through review of hospital files. They additionally completed Historical-Clinical-Risk Management – 20 (HCR-20) and the Hare Psychopathy Checklist: Screening Version (PCL:SV) assessments. Outcome data was coded from hospital files for a 12-month follow-up period using the Overt Aggression Scale (OAS). START assessments evidenced excellent interrater reliability and demonstrated both predictive and incremental validity over the HCR-20 Historical subscale scores and PCL:SV total scores. Overall, results support the reliability and validity of START assessments, and use of the structured professional judgment approach more broadly, as well as the value of using dynamic risk and protective factors to assess violence risk. PMID:22250595
Updating Risk Prediction Tools: A Case Study in Prostate Cancer
Ankerst, Donna P.; Koniarski, Tim; Liang, Yuanyuan; Leach, Robin J.; Feng, Ziding; Sanda, Martin G.; Partin, Alan W.; Chan, Daniel W; Kagan, Jacob; Sokoll, Lori; Wei, John T; Thompson, Ian M.
2013-01-01
Online risk prediction tools for common cancers are now easily accessible and widely used by patients and doctors for informed decision-making concerning screening and diagnosis. A practical problem is as cancer research moves forward and new biomarkers and risk factors are discovered, there is a need to update the risk algorithms to include them. Typically the new markers and risk factors cannot be retrospectively measured on the same study participants used to develop the original prediction tool, necessitating the merging of a separate study of different participants, which may be much smaller in sample size and of a different design. Validation of the updated tool on a third independent data set is warranted before the updated tool can go online. This article reports on the application of Bayes rule for updating risk prediction tools to include a set of biomarkers measured in an external study to the original study used to develop the risk prediction tool. The procedure is illustrated in the context of updating the online Prostate Cancer Prevention Trial Risk Calculator to incorporate the new markers %freePSA and [−2]proPSA measured on an external case control study performed in Texas, U.S.. Recent state-of-the art methods in validation of risk prediction tools and evaluation of the improvement of updated to original tools are implemented using an external validation set provided by the U.S. Early Detection Research Network. PMID:22095849
Updating risk prediction tools: a case study in prostate cancer.
Ankerst, Donna P; Koniarski, Tim; Liang, Yuanyuan; Leach, Robin J; Feng, Ziding; Sanda, Martin G; Partin, Alan W; Chan, Daniel W; Kagan, Jacob; Sokoll, Lori; Wei, John T; Thompson, Ian M
2012-01-01
Online risk prediction tools for common cancers are now easily accessible and widely used by patients and doctors for informed decision-making concerning screening and diagnosis. A practical problem is as cancer research moves forward and new biomarkers and risk factors are discovered, there is a need to update the risk algorithms to include them. Typically, the new markers and risk factors cannot be retrospectively measured on the same study participants used to develop the original prediction tool, necessitating the merging of a separate study of different participants, which may be much smaller in sample size and of a different design. Validation of the updated tool on a third independent data set is warranted before the updated tool can go online. This article reports on the application of Bayes rule for updating risk prediction tools to include a set of biomarkers measured in an external study to the original study used to develop the risk prediction tool. The procedure is illustrated in the context of updating the online Prostate Cancer Prevention Trial Risk Calculator to incorporate the new markers %freePSA and [-2]proPSA measured on an external case-control study performed in Texas, U.S.. Recent state-of-the art methods in validation of risk prediction tools and evaluation of the improvement of updated to original tools are implemented using an external validation set provided by the U.S. Early Detection Research Network. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Austin, S. Bryn; Pazaris, Mathew J.; Rosner, Bernard; Bowen, Deborah; Rich-Edwards, Janet; Spiegelman, Donna
2012-01-01
Background Lesbian and bisexual women may be at greater risk of breast cancer than heterosexual women during the premenopausal period due to disparities in risk factors. Methods With 16 years of prospective data from a large cohort of U.S. women ages 25–58 years, we conducted a breast cancer risk assessment for 87,392 premenopausal women by applying the Rosner-Colditz biomathematical risk-prediction model to estimate breast cancer risk based on known risk factors. Based on each woman’s comprehensive risk factor profile, we calculated the predicted one-year incidence rate (IR) per 100,000 person-years and estimated incidence rate ratios (IRR) and 95% confidence intervals (CI) for lesbian and bisexual women compared to heterosexual women. Results 87,392 premenopausal women provided 1,091,871 person-years of data included in analyses. Mean predicted one-year breast cancer IRs per 100,000 person-years for each sexual orientation group were: heterosexual 122.55, lesbian 131.61, and bisexual 131.72. IRs were significantly elevated in both lesbian (IRR 1.06; 95 CI 1.06, 1.06) and bisexual (IRR 1.10; 95% CI 1.10, 1.10) women compared to heterosexual women. Conclusions Our findings suggest both lesbian and bisexual women have slightly elevated predicted breast cancer incidence compared to heterosexual women throughout the premenopausal period. Impact Health professionals must ensure that breast cancer prevention efforts are reaching these women. As more health systems around the country collect data on patient sexual orientation, the National Cancer Institute’s SEER cancer registry should add this information to its data system to monitor progress in reducing sexual orientation-related disparities in cancer incidence and mortality. PMID:23035180
Leptospirosis in American Samoa – Estimating and Mapping Risk Using Environmental Data
Lau, Colleen L.; Clements, Archie C. A.; Skelly, Chris; Dobson, Annette J.; Smythe, Lee D.; Weinstein, Philip
2012-01-01
Background The recent emergence of leptospirosis has been linked to many environmental drivers of disease transmission. Accurate epidemiological data are lacking because of under-diagnosis, poor laboratory capacity, and inadequate surveillance. Predictive risk maps have been produced for many diseases to identify high-risk areas for infection and guide allocation of public health resources, and are particularly useful where disease surveillance is poor. To date, no predictive risk maps have been produced for leptospirosis. The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors, produce a predictive disease risk map for American Samoa, and assess the accuracy of the maps in predicting infection risk. Methodology and Principal Findings Data on seroprevalence and risk factors were obtained from a recent study of leptospirosis in American Samoa. Data on environmental variables were obtained from local sources, and included rainfall, altitude, vegetation, soil type, and location of backyard piggeries. Multivariable logistic regression was performed to investigate associations between seropositivity and risk factors. Using the multivariable models, seroprevalence at geographic locations was predicted based on environmental variables. Goodness of fit of models was measured using area under the curve of the receiver operating characteristic, and the percentage of cases correctly classified as seropositive. Environmental predictors of seroprevalence included living below median altitude of a village, in agricultural areas, on clay soil, and higher density of piggeries above the house. Models had acceptable goodness of fit, and correctly classified ∼84% of cases. Conclusions and Significance Environmental variables could be used to identify high-risk areas for leptospirosis. Environmental monitoring could potentially be a valuable strategy for leptospirosis control, and allow us to move from disease surveillance to environmental health hazard surveillance as a more cost-effective tool for directing public health interventions. PMID:22666516
A Review on Automatic Mammographic Density and Parenchymal Segmentation
He, Wenda; Juette, Arne; Denton, Erika R. E.; Oliver, Arnau
2015-01-01
Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause(s) of breast cancer still remains unknown. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective way to tackle breast cancer. There are more than 70 common genetic susceptibility factors included in the current non-image-based risk prediction models (e.g., the Gail and the Tyrer-Cuzick models). Image-based risk factors, such as mammographic densities and parenchymal patterns, have been established as biomarkers but have not been fully incorporated in the risk prediction models used for risk stratification in screening and/or measuring responsiveness to preventive approaches. Within computer aided mammography, automatic mammographic tissue segmentation methods have been developed for estimation of breast tissue composition to facilitate mammographic risk assessment. This paper presents a comprehensive review of automatic mammographic tissue segmentation methodologies developed over the past two decades and the evidence for risk assessment/density classification using segmentation. The aim of this review is to analyse how engineering advances have progressed and the impact automatic mammographic tissue segmentation has in a clinical environment, as well as to understand the current research gaps with respect to the incorporation of image-based risk factors in non-image-based risk prediction models. PMID:26171249
Toward a cumulative ecological risk model for the etiology of child maltreatment
MacKenzie, Michael J.; Kotch, Jonathan B.; Lee, Li-Ching
2011-01-01
The purpose of the current study was to further the integration of cumulative risk models with empirical research on the etiology of child maltreatment. Despite the well-established literature supporting the importance of the accumulation of ecological risk, this perspective has had difficulty infiltrating empirical maltreatment research and its tendency to focus on more limited risk factors. Utilizing a sample of 842 mother-infant dyads, we compared the capacity of individual risk factors and a cumulative index to predict maltreatment reports in a prospective longitudinal investigation over the first sixteen years of life. The total load of risk in early infancy was found to be related to maternal cognitions surrounding her new role, measures of social support and well-being, and indicators of child cognitive functioning. After controlling for total level of cumulative risk, most single factors failed to predict later maltreatment reports and no single variable provided odd-ratios as powerful as the predictive power of a cumulative index. Continuing the shift away from simplistic causal models toward an appreciation for the cumulative nature of risk would be an important step forward in the way we conceptualize intervention and support programs, concentrating them squarely on alleviating the substantial risk facing so many of society’s families. PMID:24817777
Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort.
Fortner, Renée T; Hüsing, Anika; Kühn, Tilman; Konar, Meric; Overvad, Kim; Tjønneland, Anne; Hansen, Louise; Boutron-Ruault, Marie-Christine; Severi, Gianluca; Fournier, Agnès; Boeing, Heiner; Trichopoulou, Antonia; Benetou, Vasiliki; Orfanos, Philippos; Masala, Giovanna; Agnoli, Claudia; Mattiello, Amalia; Tumino, Rosario; Sacerdote, Carlotta; Bueno-de-Mesquita, H B As; Peeters, Petra H M; Weiderpass, Elisabete; Gram, Inger T; Gavrilyuk, Oxana; Quirós, J Ramón; Maria Huerta, José; Ardanaz, Eva; Larrañaga, Nerea; Lujan-Barroso, Leila; Sánchez-Cantalejo, Emilio; Butt, Salma Tunå; Borgquist, Signe; Idahl, Annika; Lundin, Eva; Khaw, Kay-Tee; Allen, Naomi E; Rinaldi, Sabina; Dossus, Laure; Gunter, Marc; Merritt, Melissa A; Tzoulaki, Ioanna; Riboli, Elio; Kaaks, Rudolf
2017-03-15
Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were selected into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including etiologic markers on independent pathways and genetic markers may further improve discrimination. © 2016 UICC.
Skrede, Turid; Stavnsbo, Mette; Aadland, Eivind; Aadland, Katrine N; Anderssen, Sigmund A; Resaland, Geir K; Ekelund, Ulf
2017-06-01
Background: Cross-sectional data have suggested an inverse relation between physical activity and cardiometabolic risk factors that is independent of sedentary time. However, little is known about which subcomponent of physical activity may predict cardiometabolic risk factors in youths. Objective: We examined the independent prospective associations between objectively measured sedentary time and subcomponents of physical activity with individual and clustered cardiometabolic risk factors in healthy children aged 10 y. Design: We included 700 children (49.1% males; 50.9% females) in which sedentary time and physical activity were measured with the use of accelerometry. Systolic blood pressure, waist circumference (WC), and fasting blood sample (total cholesterol, high-density lipoprotein cholesterol, triglycerides, glucose, fasting insulin) were measured with the use of standard clinical methods and analyzed individually and as a clustered cardiometabolic risk score standardized by age and sex ( z score). Exposure and outcome variables were measured at baseline and at follow-up 7 mo later. Results: Sedentary time was not associated with any of the individual cardiometabolic risk factors or clustered cardiometabolic risk in prospective analyses. Moderate physical activity at baseline predicted lower concentrations of triglycerides ( P = 0.021) and homeostatic model assessment for insulin resistance ( P = 0.027) at follow-up independent of sex, socioeconomic status, Tanner stage, monitor wear time, or WC. Moderate-to-vigorous physical activity ( P = 0.043) and vigorous physical activity ( P = 0.028) predicted clustered cardiometabolic risk at follow-up, but these associations were attenuated after adjusting for WC. Conclusions: Physical activity, but not sedentary time, is prospectively associated with cardiometabolic risk in healthy children. Public health strategies aimed at improving children's cardiometabolic profile should strive for increasing physical activity of at least moderate intensity rather than reducing sedentary time. This trial was registered at clinicaltrials.gov as NCT02132494. © 2017 American Society for Nutrition.
Rispo, Antonio; Imperatore, Nicola; Testa, Anna; Bucci, Luigi; Luglio, Gaetano; De Palma, Giovanni Domenico; Rea, Matilde; Nardone, Olga Maria; Caporaso, Nicola; Castiglione, Fabiana
2018-03-08
In the management of Crohn's Disease (CD) patients, having a simple score combining clinical, endoscopic and imaging features to predict the risk of surgery could help to tailor treatment more effectively. AIMS: to prospectively evaluate the one-year risk factors for surgery in refractory/severe CD and to generate a risk matrix for predicting the probability of surgery at one year. CD patients needing a disease re-assessment at our tertiary IBD centre underwent clinical, laboratory, endoscopy and bowel sonography (BS) examinations within one week. The optimal cut-off values in predicting surgery were identified using ROC curves for Simple Endoscopic Score for CD (SES-CD), bowel wall thickness (BWT) at BS, and small bowel CD extension at BS. Binary logistic regression and Cox's regression were then carried out. Finally, the probabilities of surgery were calculated for selected baseline levels of covariates and results were arranged in a prediction matrix. Of 100 CD patients, 30 underwent surgery within one year. SES-CD©9 (OR 15.3; p<0.001), BWT©7 mm (OR 15.8; p<0.001), small bowel CD extension at BS©33 cm (OR 8.23; p<0.001) and stricturing/penetrating behavior (OR 4.3; p<0.001) were the only independent factors predictive of surgery at one-year based on binary logistic and Cox's regressions. Our matrix model combined these risk factors and the probability of surgery ranged from 0.48% to 87.5% (sixteen combinations). Our risk matrix combining clinical, endoscopic and ultrasonographic findings can accurately predict the one-year risk of surgery in patients with severe/refractory CD requiring a disease re-evaluation. This tool could be of value in clinical practice, serving as the basis for a tailored management of CD patients.
Weighted Genetic Risk Scores and Prediction of Weight Gain in Solid Organ Transplant Populations
Saigi-Morgui, Núria; Quteineh, Lina; Bochud, Pierre-Yves; Crettol, Severine; Kutalik, Zoltán; Wojtowicz, Agnieszka; Bibert, Stéphanie; Beckmann, Sonja; Mueller, Nicolas J; Binet, Isabelle; van Delden, Christian; Steiger, Jürg; Mohacsi, Paul; Stirnimann, Guido; Soccal, Paola M.; Pascual, Manuel; Eap, Chin B
2016-01-01
Background Polygenic obesity in Solid Organ Transplant (SOT) populations is considered a risk factor for the development of metabolic abnormalities and graft survival. Few studies to date have studied the genetics of weight gain in SOT recipients. We aimed to determine whether weighted genetic risk scores (w-GRS) integrating genetic polymorphisms from GWAS studies (SNP group#1 and SNP group#2) and from Candidate Gene studies (SNP group#3) influence BMI in SOT populations and if they predict ≥10% weight gain (WG) one year after transplantation. To do so, two samples (nA = 995, nB = 156) were obtained from naturalistic studies and three w-GRS were constructed and tested for association with BMI over time. Prediction of 10% WG at one year after transplantation was assessed with models containing genetic and clinical factors. Results w-GRS were associated with BMI in sample A and B combined (BMI increased by 0.14 and 0.11 units per additional risk allele in SNP group#1 and #2, respectively, p-values<0.008). w-GRS of SNP group#3 showed an effect of 0.01 kg/m2 per additional risk allele when combining sample A and B (p-value 0.04). Models with genetic factors performed better than models without in predicting 10% WG at one year after transplantation. Conclusions This is the first study in SOT evaluating extensively the association of w-GRS with BMI and the influence of clinical and genetic factors on 10% of WG one year after transplantation, showing the importance of integrating genetic factors in the final model. Genetics of obesity among SOT recipients remains an important issue and can contribute to treatment personalization and prediction of WG after transplantation. PMID:27788139
Weighted Genetic Risk Scores and Prediction of Weight Gain in Solid Organ Transplant Populations.
Saigi-Morgui, Núria; Quteineh, Lina; Bochud, Pierre-Yves; Crettol, Severine; Kutalik, Zoltán; Wojtowicz, Agnieszka; Bibert, Stéphanie; Beckmann, Sonja; Mueller, Nicolas J; Binet, Isabelle; van Delden, Christian; Steiger, Jürg; Mohacsi, Paul; Stirnimann, Guido; Soccal, Paola M; Pascual, Manuel; Eap, Chin B
2016-01-01
Polygenic obesity in Solid Organ Transplant (SOT) populations is considered a risk factor for the development of metabolic abnormalities and graft survival. Few studies to date have studied the genetics of weight gain in SOT recipients. We aimed to determine whether weighted genetic risk scores (w-GRS) integrating genetic polymorphisms from GWAS studies (SNP group#1 and SNP group#2) and from Candidate Gene studies (SNP group#3) influence BMI in SOT populations and if they predict ≥10% weight gain (WG) one year after transplantation. To do so, two samples (nA = 995, nB = 156) were obtained from naturalistic studies and three w-GRS were constructed and tested for association with BMI over time. Prediction of 10% WG at one year after transplantation was assessed with models containing genetic and clinical factors. w-GRS were associated with BMI in sample A and B combined (BMI increased by 0.14 and 0.11 units per additional risk allele in SNP group#1 and #2, respectively, p-values<0.008). w-GRS of SNP group#3 showed an effect of 0.01 kg/m2 per additional risk allele when combining sample A and B (p-value 0.04). Models with genetic factors performed better than models without in predicting 10% WG at one year after transplantation. This is the first study in SOT evaluating extensively the association of w-GRS with BMI and the influence of clinical and genetic factors on 10% of WG one year after transplantation, showing the importance of integrating genetic factors in the final model. Genetics of obesity among SOT recipients remains an important issue and can contribute to treatment personalization and prediction of WG after transplantation.
Predicting preterm birth among participants of North Carolina’s Pregnancy Medical Home Program
Tucker, Christine M.; Berrien, Kate; Menard, M. Kathryn; Herring, Amy H.; Daniels, Julie; Rowley, Diane L.; Halpern, Carolyn Tucker
2016-01-01
Objective To determine which combination of risk factors from Community Care of North Carolina’s (CCNC) Pregnancy Medical Home (PMH) risk screening form was most predictive of preterm birth (PTB) by parity and race/ethnicity. Methods This retrospective cohort included pregnant Medicaid patients screened by the PMH program before 24 weeks gestation who delivered a live birth in North Carolina between September 2011-September 2012 (N=15,428). Data came from CCNC’s Case Management Information System, Medicaid claims, and birth certificates. Logistic regression with backward stepwise elimination was used to arrive at the final models. To internally validate the predictive model, we used bootstrapping techniques. Results The prevalence of PTB was 11%. Multifetal gestation, a previous PTB, cervical insufficiency, diabetes, renal disease, and hypertension were the strongest risk factors with odds ratios ranging from 2.34 to 10.78. Non-Hispanic black race, underweight, smoking during pregnancy, asthma, other chronic conditions, nulliparity, and a history of a low birth weight infant or fetal death/second trimester loss were additional predictors in the final predictive model. About half of the risk factors prioritized by the PMH program remained in our final model (ROC=0.66). The odds of PTB associated with food insecurity and obesity differed by parity. The influence of unsafe or unstable housing and short interpregnancy interval on PTB differed by race/ethnicity. Conclusions Evaluation of the PMH risk screen provides insight to ensure women at highest risk are prioritized for care management. Using multiple data sources, salient risk factors for PTB were identified, allowing for better-targeted approaches for PTB prevention. PMID:26112751
Examining overgeneral autobiographical memory as a risk factor for adolescent depression.
Rawal, Adhip; Rice, Frances
2012-05-01
Identifying risk factors for adolescent depression is an important research aim. Overgeneral autobiographical memory (OGM) is a feature of adolescent depression and a candidate cognitive risk factor for future depression. However, no study has ascertained whether OGM predicts the onset of adolescent depressive disorder. OGM was investigated as a predictor of depressive disorder and symptoms in a longitudinal study of high-risk adolescents. In addition, cross-sectional associations between OGM and current depression and OGM differences between depressed adolescents with different clinical outcomes were examined over time. A 1-year longitudinal study of adolescents at familial risk for depression (n = 277, 10-18 years old) was conducted. Autobiographical memory was assessed at baseline. Clinical interviews assessed diagnostic status at baseline and follow-up. Currently depressed adolescents showed an OGM bias compared with adolescents with no disorder and those with anxiety or externalizing disorders. OGM to negative cues predicted the onset of depressive disorder and depressive symptoms at follow-up in adolescents free from depressive disorder at baseline. This effect was independent of the contribution of age, IQ, and baseline depressive symptoms. OGM did not predict onset of anxiety or externalizing disorders. Adolescents with depressive disorder at both assessments were not more overgeneral than adolescents who recovered from depressive disorder over the follow-up period. OGM to negative cues predicted the onset of depressive disorder (but not other disorders) and depressive symptoms over time in adolescents at familial risk for depression. Results are consistent with OGM as a risk factor for depression. Copyright © 2012 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.
Factors predicting high estimated 10-year stroke risk: thai epidemiologic stroke study.
Hanchaiphiboolkul, Suchat; Puthkhao, Pimchanok; Towanabut, Somchai; Tantirittisak, Tasanee; Wangphonphatthanasiri, Khwanrat; Termglinchan, Thanes; Nidhinandana, Samart; Suwanwela, Nijasri Charnnarong; Poungvarin, Niphon
2014-08-01
The purpose of the study was to determine the factors predicting high estimated 10-year stroke risk based on a risk score, and among the risk factors comprising the risk score, which factors had a greater impact on the estimated risk. Thai Epidemiologic Stroke study was a community-based cohort study, which recruited participants from the general population from 5 regions of Thailand. Cross-sectional baseline data of 16,611 participants aged 45-69 years who had no history of stroke were included in this analysis. Multiple logistic regression analysis was used to identify the predictors of high estimated 10-year stroke risk based on the risk score of the Japan Public Health Center Study, which estimated the projected 10-year risk of incident stroke. Educational level, low personal income, occupation, geographic area, alcohol consumption, and hypercholesterolemia were significantly associated with high estimated 10-year stroke risk. Among these factors, unemployed/house work class had the highest odds ratio (OR, 3.75; 95% confidence interval [CI], 2.47-5.69) followed by illiterate class (OR, 2.30; 95% CI, 1.44-3.66). Among risk factors comprising the risk score, the greatest impact as a stroke risk factor corresponded to age, followed by male sex, diabetes mellitus, systolic blood pressure, and current smoking. Socioeconomic status, in particular, unemployed/house work and illiterate class, might be good proxy to identify the individuals at higher risk of stroke. The most powerful risk factors were older age, male sex, diabetes mellitus, systolic blood pressure, and current smoking. Copyright © 2014 National Stroke Association. Published by Elsevier Inc. All rights reserved.
Child-Related Cognitions and Affective Functioning of Physically Abusive and Comparison Parents.
ERIC Educational Resources Information Center
Haskett, Mary E.; Scott, Susan Smith; Grant, Raven; Ward, Caryn Sabourin; Robinson, Canby
2003-01-01
This study examined risk factors for abusive parenting in 56 physically abusive parents and 62 matched comparison parents. The set of five risk variables was predictive of abuse status; however, not all variables were predictive when considered individually and interactions did not contribute significantly to prediction. Findings supported a…
Kudumija Slijepcevic, Marija; Jukic, Vlado; Novalic, Darko; Zarkovic-Palijan, Tija; Milosevic, Milan; Rosenzweig, Ivana
2014-04-01
To determine predictive risk factors for violent offending in patients with paranoid schizophrenia in Croatia. The cross-sectional study including male in-patients with paranoid schizophrenia with (N=104) and without (N=102) history of physical violence and violent offending was conducted simultaneously in several hospitals in Croatia during one-year period (2010-2011). Data on their sociodemographic characteristics, duration of untreated illness phase (DUP), alcohol abuse, suicidal behavior, personality features, and insight into illness were collected and compared between groups. Binary logistic regression model was used to determine the predictors of violent offending. Predictors of violent offending were older age, DUP before first contact with psychiatric services, and alcohol abuse. Regression model showed that the strongest positive predictive factor was harmful alcohol use, as determined by AUDIT test (odds ratio 37.01; 95% confidence interval 5.20-263.24). Psychopathy, emotional stability, and conscientiousness were significant positive predictive factors, while extroversion, pleasantness, and intellect were significant negative predictive factors for violent offending. This study found an association between alcohol abuse and the risk for violent offending in paranoid schizophrenia. We hope that this finding will help improve public and mental health prevention strategies in this vulnerable patient group.
Resilient parenting of children at developmental risk across middle childhood.
Ellingsen, Ruth; Baker, Bruce L; Blacher, Jan; Crnic, Keith
2014-06-01
This paper focuses on factors that might influence positive parenting during middle childhood when a parent faces formidable challenges defined herein as "resilient parenting." Data were obtained from 162 families at child age 5 and 8 years. Using an adapted ABCX model, we examined three risk domains (child developmental delay, child ADHD/ODD diagnosis, and low family income) and three protective factors (mother's education, health, and optimism). The outcome of interest was positive parenting as coded from mother-child interactions. We hypothesized that each of the risk factors would predict poorer parenting and that higher levels of each protective factor would buffer the risk-parenting relationship. Positive parenting scores decreased across levels of increasing risk. Maternal optimism appeared to be a protective factor for resilient parenting concurrently at age 5 and predictively to age 8, as well as a predictor of positive change in parenting from age 5 to age 8, above and beyond level of risk. Maternal education and health were not significantly protective for positive parenting. Limitations, future directions, and implications for intervention are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.
Resilient Parenting of Children at Developmental Risk Across Middle Childhood
Baker, Bruce L.; Blacher, Jan; Crnic, Keith
2015-01-01
This paper focuses on factors that might influence positive parenting during middle childhood when a parent faces formidable challenges defined herein as “resilient parenting.” Data were obtained from 162 families at child age 5 and 8 years. Using an adapted ABCX model, we examined three risk domains (child developmental delay, child ADHD/ODD diagnosis, and low family income) and three protective factors (mother’s education, health, and optimism). The outcome of interest was positive parenting as coded from mother-child interactions. We hypothesized that each of the risk factors would predict poorer parenting and that higher levels of each protective factor would buffer the risk-parenting relationship. Positive parenting scores decreased across levels of increasing risk. Maternal optimism appeared to be a protective factor for resilient parenting concurrently at age 5 and predictively to age 8, as well as a predictor of positive change in parenting from age 5 to age 8, above and beyond level of risk. Maternal education and health were not significantly protective for positive parenting. Limitations, future directions, and implications for intervention are discussed. PMID:24713516
A summary risk score for the prediction of Alzheimer disease in elderly persons.
Reitz, Christiane; Tang, Ming-Xin; Schupf, Nicole; Manly, Jennifer J; Mayeux, Richard; Luchsinger, José A
2010-07-01
To develop a simple summary risk score for the prediction of Alzheimer disease in elderly persons based on their vascular risk profiles. A longitudinal, community-based study. New York, New York. Patients One thousand fifty-one Medicare recipients aged 65 years or older and residing in New York who were free of dementia or cognitive impairment at baseline. We separately explored the associations of several vascular risk factors with late-onset Alzheimer disease (LOAD) using Cox proportional hazards models to identify factors that would contribute to the risk score. Then we estimated the score values of each factor based on their beta coefficients and created the LOAD vascular risk score by summing these individual scores. Risk factors contributing to the risk score were age, sex, education, ethnicity, APOE epsilon4 genotype, history of diabetes, hypertension or smoking, high-density lipoprotein levels, and waist to hip ratio. The resulting risk score predicted dementia well. According to the vascular risk score quintiles, the risk to develop probable LOAD was 1.0 for persons with a score of 0 to 14 and increased 3.7-fold for persons with a score of 15 to 18, 3.6-fold for persons with a score of 19 to 22, 12.6-fold for persons with a score of 23 to 28, and 20.5-fold for persons with a score higher than 28. While additional studies in other populations are needed to validate and further develop the score, our study suggests that this vascular risk score could be a valuable tool to identify elderly individuals who might be at risk of LOAD. This risk score could be used to identify persons at risk of LOAD, but can also be used to adjust for confounders in epidemiologic studies.
2013-01-01
Background Accidental falls in the elderly are a major health problem, despite extensive research on risk factors and prevention. Only a limited number of multifactorial, long-term prospective studies have been performed on risk factors for falls in the general elderly population. The aim of this study was to identify risk factors predicting falls in a general elderly population after three and six years, using a prospective design. Methods The prevalence of 38 risk factors was recorded at a baseline assessment of 1763 subjects (aged 60–93 years). The incidence of one or more falls was recorded after three and six years. The predicted risk of falling, after exposure to the various risk factors, was analysed in a multiple logistic regression model, adjusted for age and sex, and presented as odds ratios (OR). A principal component analysis (PCA), including the statistical significant factors, was also performed to identify thematic, uncorrelated components associated with falls. Results The use of neuroleptics (OR 3.30, 95% CI: 1.15–9.43), heart failure with symptoms (OR 1.88, 95% CI: 1.17–3.04) and low walking speed (OR 1.77, 95% CI: 1.28–2.46) were prominent individual risk factors for falls. In the PCA, three main components predicting falls were identified: reduced mobility, OR 2.12 (95% CI 1.54–2.91), heart dysfunction, OR 1.66 (95% CI 1.26–2.20) and functional impairment including nocturia, OR 1.38 (95% CI 1.01-1.88). Conclusions Three main components predicting falls were identified in a general elderly population after three and six years: reduced mobility, heart dysfunction and functional impairment including nocturia. The use of neuroleptic drugs was also a prominent individual risk factor, although the prevalence was low. Heart failure with symptoms was a significant risk factor for falls and may be of clinical importance as the prevalence of this condition in the elderly is increasing worldwide. There is need for further research on the relation between heart failure and falls in the elderly, as the treatment for this condition is poorly documented in this demographic. The findings of this study may be valuable in the development of intervention programmes aimed at sustainable, long-term reduction of falls in the elderly. PMID:23919320
Serum creatinine role in predicting outcome after cardiac surgery beyond acute kidney injury
Najafi, Mahdi
2014-01-01
Serum creatinine is still the most important determinant in the assessment of perioperative renal function and in the prediction of adverse outcome in cardiac surgery. Many biomarkers have been studied to date; still, there is no surrogate for serum creatinine measurement in clinical practice because it is feasible and inexpensive. High levels of serum creatinine and its equivalents have been the most important preoperative risk factor for postoperative renal injury. Moreover, creatinine is the mainstay in predicting risk models and risk factor reduction has enhanced its importance in outcome prediction. The future perspective is the development of new definitions and novel tools for the early diagnosis of acute kidney injury largely based on serum creatinine and a panel of novel biomarkers. PMID:25276301
Burgos, Miria Suzana; Burgos, Leandro Tibiriçá; Camargo, Marcelo Dias; Franke, Silvia Isabel Rech; Prá, Daniel; da Silva, Antônio Marcos Vargas; Borges, Tássia Silvana; Todendi, Pâmela Ferreira; Reckziegel, Miriam Beatris; Reuter, Cézane Priscila
2013-01-01
Background Obesity has been identified as an important risk factor in the development of cardiovascular diseases; however, other factors, combined or not with obesity, can influence cardiovascular risk and should be considered in cardiovascular risk stratification in pediatrics. Objective To analyze the association between anthropometry measures and cardiovascular risk factors, to investigate the determinants to changes in blood pressure (BP), and to propose a prediction equation to waist circumference (WC) in children and adolescents. Methods We evaluated 1,950 children and adolescents, aged 7 to 18 years. Visceral fat was assessed by WC and waist hip relationship, BP and body mass index (BMI). In a randomly selected subsample of these volunteers (n = 578), total cholesterol, glucose and triglycerides levels were evaluated. Results WC was positively correlated with BMI (r = 0.85; p < 0.001) and BP (SBP r = 0.45 and DBP = 0.37; p < 0.001). Glycaemia and triglycerides showed a weak correlation with WC (r = 0.110; p = 0.008 e r = 0.201; p < 0.001, respectively). Total cholesterol did not correlate with any of the variables. Age, BMI and WC were significant predictors on the regression models for BP (p < 0.001). We propose a WC prediction equation for children and adolescents: boys: y = 17.243 + 0.316 (height in cm); girls: y = 25.197 + 0.256 (height in cm). Conclusion WC is associated with cardiovascular risk factors and presents itself as a risk factor predictor of hypertension in children and adolescents. The WC prediction equation proposed by us should be tested in future studies. PMID:23979777
[Epidemiology of shoulder dystocia].
Deneux-Tharaux, C; Delorme, P
2015-12-01
To synthetize the available evidence regarding the incidence and risk factors of shoulder dystocia (SD). Consultation of the Medline database, and of national guidelines. Shoulder dystocia is defined as a vaginal delivery that requires additional obstetric manoeuvres to deliver the foetus after the head has delivered and gentle traction has failed. With this definition, the incidence of SD in population-based studies is about 0.5-1% of vaginal deliveries. Many risk factors have been described but most associations are not independent, or have not been constantly found. The 2 characteristics consistently found as independent risk factors for SD in the literature are previous SD (incidence of SD of about 10% in parturients with previous SD) and foetal macrosomia. Maternal diabetes and obesity also are associated with a higher risk of SD (2 to 4 folds) but these associations may be completely explained by foetal macrosomia. However, even factors independently and constantly associated with SD do not allow a valid prediction of SD because they are not discriminant; 50 to 70% of SD cases occur in their absence, and the great majority of deliveries when they are present is not associated with SD. Shoulder dystocia is defined by the need for additional obstetric manoeuvres to deliver the foetus after the head has delivered and gentle traction has failed, and complicates 0.5-1% of vaginal deliveries. Its main risk factors are previous SD and macrosomia, but they are poorly predictive. SD remains a non-predictable obstetrics emergency. Knowledge of SD risk factors should increase the vigilance of clinicians in at-risk contexts. Copyright © 2015. Published by Elsevier Masson SAS.
Hardt, J; Bernert, S; Matschinger, H; Angermeier, M C; Vilagut, G; Bruffaerts, R; de Girolamo, G; de Graaf, R; Haro, J M; Kovess, V; Alonso, J
2015-04-01
Suicidality constitutes a major health concern in many countries. The aim of the present paper was to analyse 10 of its risk factors and their interdependence. Data on suicidality, mental disorders and experience of childhood violence was collected from 8796 respondents in the European Study of the Epidemiology of Mental Disorders (ESEMeD). The CIDI was used to assess mental disorders. Individuals were randomly divided into two subgroups. In one, a Graphical Markov model to predict suicidality was constructed, in the second, predictors were cross-validated. Lifetime suicidality was predicted mainly by lifetime depression and early experiences of violence, with a pseudo R-square of 12.8%. In addition, alcohol disorders predicted suicidality, but played a minor role compared with the other risk factors in this sample. In addition to depression, early experience of violence constitutes an important risk factor of suicidality. This is a cross-sectional and retrospective study assessing risk factors for suicidality, not for suicide itself. Copyright © 2015 Elsevier B.V. All rights reserved.
Eisenbarth, Hedwig; Osterheider, Michael; Nedopil, Norbert; Stadtland, Cornelis
2012-01-01
A clear and structured approach to evidence-based and gender-specific risk assessment of violence in female offenders is high on political and mental health agendas. However, most data on the factors involved in risk-assessment instruments are based on data of male offenders. The aim of the present study was to validate the use of the Psychopathy Checklist Revised (PCL-R), the HCR-20 and the Violence Risk Appraisal Guide (VRAG) for the prediction of recidivism in German female offenders. This study is part of the Munich Prognosis Project (MPP). It focuses on a subsample of female delinquents (n = 80) who had been referred for forensic-psychiatric evaluation prior to sentencing. The mean time at risk was 8 years (SD = 5 years; range: 1-18 years). During this time, 31% (n = 25) of the female offenders were reconvicted, 5% (n = 4) for violent and 26% (n = 21) for non-violent re-offenses. The predictive validity of the PCL-R for general recidivism was calculated. Analysis with receiver-operating characteristics revealed that the PCL-R total score, the PCL-R antisocial lifestyle factor, the PCL-R lifestyle factor and the PCL-R impulsive and irresponsible behavioral style factor had a moderate predictive validity for general recidivism (area under the curve, AUC = 0.66, p = 0.02). The VRAG has also demonstrated predictive validity (AUC = 0.72, p = 0.02), whereas the HCR-20 showed no predictive validity. These results appear to provide the first evidence that the PCL-R total score and the antisocial lifestyle factor are predictive for general female recidivism, as has been shown consistently for male recidivists. The implications of these findings for crime prevention, prognosis in women, and future research are discussed. Copyright © 2012 John Wiley & Sons, Ltd.
Neonatal Candidiasis: Epidemiology, Risk Factors, and Clinical Judgment
Benjamin, Daniel K.; Stoll, Barbara J.; Gantz, Marie G.; Walsh, Michele C.; Sanchez, Pablo J.; Das, Abhik; Shankaran, Seetha; Higgins, Rosemary D.; Auten, Kathy J.; Miller, Nancy A.; Walsh, Thomas J.; Laptook, Abbot R.; Carlo, Waldemar A.; Kennedy, Kathleen A.; Finer, Neil N.; Duara, Shahnaz; Schibler, Kurt; Chapman, Rachel L.; Van Meurs, Krisa P.; Frantz, Ivan D.; Phelps, Dale L.; Poindexter, Brenda B.; Bell, Edward F.; O’Shea, T. Michael; Watterberg, Kristi L.; Goldberg, Ronald N.
2011-01-01
OBJECTIVE Invasive candidiasis is a leading cause of infection-related morbidity and mortality in extremely low-birth-weight (<1000 g) infants. We quantify risk factors predicting infection in high-risk premature infants and compare clinical judgment with a prediction model of invasive candidiasis. METHODS The study involved a prospective observational cohort of infants <1000 g birth weight at 19 centers of the NICHD Neonatal Research Network. At each sepsis evaluation, clinical information was recorded, cultures obtained, and clinicians prospectively recorded their estimate of the probability of invasive candidiasis. Two models were generated with invasive candidiasis as their outcome: 1) potentially modifiable risk factors and 2) a clinical model at time of blood culture to predict candidiasis. RESULTS Invasive candidiasis occurred in 137/1515 (9.0%) infants and was documented by positive culture from ≥ 1 of these sources: blood (n=96), cerebrospinal fluid (n=9), urine obtained by catheterization (n=52), or other sterile body fluid (n=10). Mortality was not different from infants who had positive blood culture compared to those with isolated positive urine culture. Incidence varied from 2–28% at the 13 centers enrolling ≥ 50 infants. Potentially modifiable risk factors (model 1) included central catheter, broad-spectrum antibiotics (e.g., third-generation cephalosporins), intravenous lipid emulsion, endotracheal tube, and antenatal antibiotics. The clinical prediction model (model 2) had an area under the receiver operating characteristic curve of 0.79, and was superior to clinician judgment (0.70) in predicting subsequent invasive candidiasis. Performance of clinical judgment did not vary significantly with level of training. CONCLUSION Prior antibiotics, presence of a central catheter, endotracheal tube, and center were strongly associated with invasive candidiasis. Modeling was more accurate in predicting invasive candidiasis than clinical judgment. PMID:20876174
Rodriguez, Christina M; Gracia, Enrique; Lila, Marisol
2016-10-01
The vast majority of research on child abuse potential has concentrated on women demonstrating varying levels of risk of perpetrating physical child abuse. In contrast, the current study considered factors predictive of physical child abuse potential in a group of 70 male intimate partner violence offenders, a group that would represent a likely high risk group. Elements of Social Information Processing theory were evaluated, including pre-existing schemas of empathy, anger, and attitudes approving of parent-child aggression considered as potential moderators of negative attributions of child behavior. To lend methodological rigor, the study also utilized multiple measures and multiple methods, including analog tasks, to predict child abuse risk. Contrary to expectations, findings did not support the role of anger independently predicting child abuse risk in this sample of men. However, preexisting beliefs approving of parent-child aggression, lower empathy, and more negative child behavior attributions independently predicted abuse potential; in addition, greater anger, poorer empathy, and more favorable attitudes toward parent-child aggression also exacerbated men's negative child attributions to further elevate their child abuse risk. Future work is encouraged to consider how factors commonly considered in women parallel or diverge from those observed to elevate child abuse risk in men of varying levels of risk. Copyright © 2016 Elsevier Ltd. All rights reserved.
Suicide Among Soldiers: A Review of Psychosocial Risk and Protective Factors
Nock, Matthew K.; Deming, Charlene A.; Fullerton, Carol S.; Gilman, Stephen E.; Goldenberg, Matthew; Kessler, Ronald C.; McCarroll, James E.; McLaughlin, Katie A.; Peterson, Christopher; Schoenbaum, Michael; Stanley, Barbara; Ursano, Robert J.
2014-01-01
Suicide is difficult to predict and prevent and remains a leading cause of death worldwide. Although soldiers historically have had a suicide rate well below that of the general population, the suicide rate among members of the U.S. Army has increased markedly over the past several years and now exceeds that of the general population. This paper reviews psychosocial factors known to be associated with the increased risk of suicidal behavior in general and describes how some of these factors may be especially important in understanding suicide among soldiers. Moving forward, the prevention of suicide requires additional research aimed at: (a) better describing when, where, and among whom suicidal behavior occurs, (b) using exploratory studies to discover new risk and protective factors, (c) developing new methods of predicting suicidal behavior that synthesize information about modifiable risk and protective factors from multiple domains, and (d) understanding the mechanisms and pathways through which suicidal behavior develops. Although the scope and severity of this problem is daunting, the increasing attention and dedication to this issue by the Armed Forces, scientists, and society provide hope for our ability to better predict and prevent these tragic outcomes in the future. PMID:23631542
Predicting urinary incontinence in women in later life: A systematic review.
Troko, Joy; Bach, Fiona; Toozs-Hobson, Philip
2016-12-01
Urinary incontinence (UI) affects 10-40% of the population and treatment costs in the UK are estimated to be £233 million per annum. A systematic review of online medical databases between July 1974 and 2016 was conducted to identify studies that had investigated risk and prediction strategies of UI in later life. Eighteen prospective longitudinal studies fulfilled the search criteria. These were analysed systematically (as per the PRISMA checklist) and bias risk through study design was minimised where possible upon data analysis. One paper proposed a predictive assessment tool called the 'continence index'. It was derived following secondary analysis of a cohort study and its predictive threshold had suboptimal sensitivity (79%) and specificity (65%) rates. Seventeen studies identified multiple strong risk factors for UI but despite a large selection of papers on the topic, no robust risk assessment tool prospectively identified patients at risk of UI in later life. Thus more research in this field is required. Clinicians should be aware particularly of modifiable UI risk factors to help reduce the clinical burden of UI in the long term. Copyright © 2016. Published by Elsevier Ireland Ltd.
Cardiac risk stratification: Role of the coronary calcium score
Sharma, Rakesh K; Sharma, Rajiv K; Voelker, Donald J; Singh, Vibhuti N; Pahuja, Deepak; Nash, Teresa; Reddy, Hanumanth K
2010-01-01
Coronary artery calcium (CAC) is an integral part of atherosclerotic coronary heart disease (CHD). CHD is the leading cause of death in industrialized nations and there is a constant effort to develop preventative strategies. The emphasis is on risk stratification and primary risk prevention in asymptomatic patients to decrease cardiovascular mortality and morbidity. The Framingham Risk Score predicts CHD events only moderately well where family history is not included as a risk factor. There has been an exploration for new tests for better risk stratification and risk factor modification. While the Framingham Risk Score, European Systematic Coronary Risk Evaluation Project, and European Prospective Cardiovascular Munster study remain excellent tools for risk factor modification, the CAC score may have additional benefit in risk assessment. There have been several studies supporting the role of CAC score for prediction of myocardial infarction and cardiovascular mortality. It has been shown to have great scope in risk stratification of asymptomatic patients in the emergency room. Additionally, it may help in assessment of progression or regression of coronary artery disease. Furthermore, the CAC score may help differentiate ischemic from nonischemic cardiomyopathy. PMID:20730016
A 6-year longitudinal study of predictors for suicide attempts in major depressive disorder.
Eikelenboom, Merijn; Beekman, Aartjan T F; Penninx, Brenda W J H; Smit, Johannes H
2018-06-13
Major depressive disorder (MDD), represent a major source of risk for suicidality. However, knowledge about risk factors for future suicide attempts (SAs) within MDD is limited. The present longitudinal study examined a wide range of putative non-clinical risk factors (demographic, social, lifestyle, personality) and clinical risk factors (depressive and suicidal indicators) for future SAs among persons with MDD. Furthermore, we examined the relationship between a number of significant predictors and the incidence of a future SA. Data are from 1713 persons (18-65 years) with a lifetime MDD at the baseline measurement of the Netherlands Study of Depression and Anxiety who were subsequently followed up 2, 4 and 6 years. SAs were assessed in the face-to-face measurements. Cox proportional hazard regression analyses were used to examine a wide range of possible non-clinical and clinical predictors for subsequent SAs during 6-year follow-up. Over a period of 6 years, 3.4% of the respondents attempted suicide. Younger age, lower education, unemployment, insomnia, antidepressant use, a previous SA and current suicidal thoughts independently predicted a future SA. The number of significant risk factors (ranging from 0 to 7) linearly predicted the incidence of future SAs: in those with 0 predictors the SA incidence was 0%, which increased to 32% incidence in those with 6+ predictors. Of the non-clinical factors, particularly socio-economic factors predicted a SA independently. Furthermore, preexisting suicidal ideation and insomnia appear to be important clinical risk factors for subsequent SA that are open to preventative intervention.
Althouse, Andrew D.; Abbott, J. Dawn; Forker, Alan D.; Bertolet, Marnie; Barinas-Mitchell, Emma; Thurston, Rebecca C.; Mulukutla, Suresh; Aboyans, Victor; Brooks, Maria Mori
2014-01-01
OBJECTIVE The aim of this article was to define risk factors for incidence of peripheral arterial disease (PAD) in a large cohort of patients with type 2 diabetes mellitus (T2DM), overall and within the context of differing glycemic control strategies. RESEARCH DESIGN AND METHODS The Bypass Angioplasty Revascularization Investigation in Type 2 Diabetes (BARI 2D) randomized controlled trial assigned participants to insulin-sensitizing (IS) therapy versus insulin-providing (IP) therapy. A total of 1,479 participants with normal ankle-brachial index (ABI) at study entry were eligible for analysis. PAD outcomes included new ABI ≤0.9 with decrease at least 0.1 from baseline, lower extremity revascularization, or lower extremity amputation. Baseline risk factors within the overall cohort and time-varying risk factors within each assigned glycemic control arm were assessed using Cox proportional hazards models. RESULTS During an average 4.6 years of follow-up, 303 participants (20.5%) experienced an incident case of PAD. Age, sex, race, and baseline smoking status were all significantly associated with incident PAD in the BARI 2D cohort. Additional baseline risk factors included pulse pressure, HbA1c, and albumin-to-creatinine ratio (P < 0.05 for each). In stratified analyses of time-varying covariates, changes in BMI, LDL, HDL, systolic blood pressure, and pulse pressure were most predictive among IS patients, while change in HbA1c was most predictive among IP patients. CONCLUSIONS Among patients with T2DM, traditional cardiovascular risk factors were the main predictors of incident PAD cases. Stratified analyses showed different risk factors were predictive for patients treated with IS medications versus those treated with IP medications. PMID:24595631
Althouse, Andrew D; Abbott, J Dawn; Forker, Alan D; Bertolet, Marnie; Barinas-Mitchell, Emma; Thurston, Rebecca C; Mulukutla, Suresh; Aboyans, Victor; Brooks, Maria Mori
2014-01-01
The aim of this article was to define risk factors for incidence of peripheral arterial disease (PAD) in a large cohort of patients with type 2 diabetes mellitus (T2DM), overall and within the context of differing glycemic control strategies. The Bypass Angioplasty Revascularization Investigation in Type 2 Diabetes (BARI 2D) randomized controlled trial assigned participants to insulin-sensitizing (IS) therapy versus insulin-providing (IP) therapy. A total of 1,479 participants with normal ankle-brachial index (ABI) at study entry were eligible for analysis. PAD outcomes included new ABI ≤0.9 with decrease at least 0.1 from baseline, lower extremity revascularization, or lower extremity amputation. Baseline risk factors within the overall cohort and time-varying risk factors within each assigned glycemic control arm were assessed using Cox proportional hazards models. During an average 4.6 years of follow-up, 303 participants (20.5%) experienced an incident case of PAD. Age, sex, race, and baseline smoking status were all significantly associated with incident PAD in the BARI 2D cohort. Additional baseline risk factors included pulse pressure, HbA1c, and albumin-to-creatinine ratio (P < 0.05 for each). In stratified analyses of time-varying covariates, changes in BMI, LDL, HDL, systolic blood pressure, and pulse pressure were most predictive among IS patients, while change in HbA1c was most predictive among IP patients. Among patients with T2DM, traditional cardiovascular risk factors were the main predictors of incident PAD cases. Stratified analyses showed different risk factors were predictive for patients treated with IS medications versus those treated with IP medications.
Claims-based risk model for first severe COPD exacerbation.
Stanford, Richard H; Nag, Arpita; Mapel, Douglas W; Lee, Todd A; Rosiello, Richard; Schatz, Michael; Vekeman, Francis; Gauthier-Loiselle, Marjolaine; Merrigan, J F Philip; Duh, Mei Sheng
2018-02-01
To develop and validate a predictive model for first severe chronic obstructive pulmonary disease (COPD) exacerbation using health insurance claims data and to validate the risk measure of controller medication to total COPD treatment (controller and rescue) ratio (CTR). A predictive model was developed and validated in 2 managed care databases: Truven Health MarketScan database and Reliant Medical Group database. This secondary analysis assessed risk factors, including CTR, during the baseline period (Year 1) to predict risk of severe exacerbation in the at-risk period (Year 2). Patients with COPD who were 40 years or older and who had at least 1 COPD medication dispensed during the year following COPD diagnosis were included. Subjects with severe exacerbations in the baseline year were excluded. Risk factors in the baseline period were included as potential predictors in multivariate analysis. Performance was evaluated using C-statistics. The analysis included 223,824 patients. The greatest risk factors for first severe exacerbation were advanced age, chronic oxygen therapy usage, COPD diagnosis type, dispensing of 4 or more canisters of rescue medication, and having 2 or more moderate exacerbations. A CTR of 0.3 or greater was associated with a 14% lower risk of severe exacerbation. The model performed well with C-statistics, ranging from 0.711 to 0.714. This claims-based risk model can predict the likelihood of first severe COPD exacerbation. The CTR could also potentially be used to target populations at greatest risk for severe exacerbations. This could be relevant for providers and payers in approaches to prevent severe exacerbations and reduce costs.
Poeran, Jashvant; Borsboom, Gerard J J M; de Graaf, Johanna P; Birnie, Erwin; Steegers, Eric A P; Bonsel, Gouke J
2015-04-01
The main objective of this study was to estimate the contributing role of maternal, child, and organizational risk factors in perinatal mortality by calculating their population attributable risks (PAR). The primary dataset comprised 1,020,749 singleton hospital births from ≥22 weeks' gestation (The Netherlands Perinatal Registry 2000-2008). PARs for single and grouped risk factors were estimated in four stages: (1) creating a duplicate dataset for each PAR analysis in which risk factors of interest were set to the most favorable value (e.g., all women assigned 'Western' for PAR calculation of ethnicity); (2) in the primary dataset an elaborate multilevel logistic regression model was fitted from which (3) the obtained coefficients were used to predict perinatal mortality in each duplicate dataset; (4) PARs were then estimated as the proportional change of predicted- compared to observed perinatal mortality. Additionally, PARs for grouped risk factors were estimated by using sequential values in two orders: after PAR estimation of grouped maternal risk factors, the resulting PARs for grouped child, and grouped organizational factors were estimated, and vice versa. The combined PAR of maternal, child and organizational factors is 94.4 %, i.e., when all factors are set to the most favorable value perinatal mortality is expected to be reduced with 94.4 %. Depending on the order of analysis, the PAR of maternal risk factors varies from 1.4 to 13.1 %, and for child- and organizational factors 58.7-74.0 and 7.3-34.3 %, respectively. In conclusion, the PAR of maternal-, child- and organizational factors combined is 94.4 %. Optimization of organizational factors may achieve a 34.3 % decrease in perinatal mortality.
Niolon, Phyllis Holditch; Vivolo-Kantor, Alana M.; Latzman, Natasha E.; Valle, Linda Anne; Kuoh, Henrietta; Burton, Tessa; Taylor, Bruce G.; Tharp, Andra T.
2018-01-01
Purpose This study describes the lifetime prevalence of teen dating violence (TDV) perpetration in a sample of middle school students from high-risk urban communities and examines the relation between TDV and related cognitive and behavioral risk factors. Methods Surveys were administered to 2,895 middle school students in four U.S. cities; 1,673 students (58%) reported having dated and were included in analyses. The sample was 52.3% female, 48.2% non-Hispanic black/African-American, 38.2% Hispanic, 4.8% non-Hispanic white, and 7.6% other race. Six types of TDV perpetration were assessed: threatening behaviors, verbal/emotional abuse, relational abuse, physical abuse, sexual abuse, and stalking. Results Of the students who had dated, 77% reported perpetrating verbal/emotional abuse, 32% reported perpetrating physical abuse, 20% reported threatening a partner, 15% reported perpetrating sexual abuse, 13% reported perpetrating relational abuse, and 6% reported stalking. Girls were more likely than boys to report perpetrating threatening behaviors, verbal/emotional abuse, and physical abuse, and boys were more likely to report perpetrating sexual abuse. Involvement in bullying positively predicted perpetration of TDV, albeit, in different ways for boys and girls. Other risk factors differed by sex. For instance, alcohol use and sex initiation predicted multiple forms of TDV perpetration for boys, whereas weapon carrying and emotional symptoms predicted several forms of TDV perpetration for girls. Conclusions The prevalence of TDV was high in our sample. Important sex differences in rates of perpetration and risk factors emerged. Comprehensive prevention programs that target TDV and related risk factors, such as bullying and other risk factors, seem warranted. PMID:25620454
Niolon, Phyllis Holditch; Vivolo-Kantor, Alana M; Latzman, Natasha E; Valle, Linda Anne; Kuoh, Henrietta; Burton, Tessa; Taylor, Bruce G; Tharp, Andra T
2015-02-01
This study describes the lifetime prevalence of teen dating violence (TDV) perpetration in a sample of middle school students from high-risk urban communities and examines the relation between TDV and related cognitive and behavioral risk factors. Surveys were administered to 2,895 middle school students in four U.S. cities; 1,673 students (58%) reported having dated and were included in analyses. The sample was 52.3% female, 48.2% non-Hispanic black/African-American, 38.2% Hispanic, 4.8% non-Hispanic white, and 7.6% other race. Six types of TDV perpetration were assessed: threatening behaviors, verbal/emotional abuse, relational abuse, physical abuse, sexual abuse, and stalking. Of the students who had dated, 77% reported perpetrating verbal/emotional abuse, 32% reported perpetrating physical abuse, 20% reported threatening a partner, 15% reported perpetrating sexual abuse, 13% reported perpetrating relational abuse, and 6% reported stalking. Girls were more likely than boys to report perpetrating threatening behaviors, verbal/emotional abuse, and physical abuse, and boys were more likely to report perpetrating sexual abuse. Involvement in bullying positively predicted perpetration of TDV, albeit, in different ways for boys and girls. Other risk factors differed by sex. For instance, alcohol use and sex initiation predicted multiple forms of TDV perpetration for boys, whereas weapon carrying and emotional symptoms predicted several forms of TDV perpetration for girls. The prevalence of TDV was high in our sample. Important sex differences in rates of perpetration and risk factors emerged. Comprehensive prevention programs that target TDV and related risk factors, such as bullying and other risk factors, seem warranted. Published by Elsevier Inc.
Shoulder Dystocia: Prediction and Management
Hill, Meghan G; Cohen, Wayne R
2016-01-01
Shoulder dystocia is a complication of vaginal delivery and the primary factor associated with brachial plexus injury. In this review, we discuss the risk factors for shoulder dystocia and propose a framework for the prediction and prevention of the complication. A recommended approach to management when shoulder dystocia occurs is outlined, with review of the maneuvers used to relieve the obstruction with minimal risk of fetal and maternal injury. PMID:26901875
McClelland, Robyn L; Jorgensen, Neal W; Budoff, Matthew; Blaha, Michael J; Post, Wendy S; Kronmal, Richard A; Bild, Diane E; Shea, Steven; Liu, Kiang; Watson, Karol E; Folsom, Aaron R; Khera, Amit; Ayers, Colby; Mahabadi, Amir-Abbas; Lehmann, Nils; Jöckel, Karl-Heinz; Moebus, Susanne; Carr, J Jeffrey; Erbel, Raimund; Burke, Gregory L
2015-10-13
Several studies have demonstrated the tremendous potential of using coronary artery calcium (CAC) in addition to traditional risk factors for coronary heart disease (CHD) risk prediction. However, to date, no risk score incorporating CAC has been developed. The goal of this study was to derive and validate a novel risk score to estimate 10-year CHD risk using CAC and traditional risk factors. Algorithm development was conducted in the MESA (Multi-Ethnic Study of Atherosclerosis), a prospective community-based cohort study of 6,814 participants age 45 to 84 years, who were free of clinical heart disease at baseline and followed for 10 years. MESA is sex balanced and included 39% non-Hispanic whites, 12% Chinese Americans, 28% African Americans, and 22% Hispanic Americans. External validation was conducted in the HNR (Heinz Nixdorf Recall Study) and the DHS (Dallas Heart Study). Inclusion of CAC in the MESA risk score offered significant improvements in risk prediction (C-statistic 0.80 vs. 0.75; p < 0.0001). External validation in both the HNR and DHS studies provided evidence of very good discrimination and calibration. Harrell's C-statistic was 0.779 in HNR and 0.816 in DHS. Additionally, the difference in estimated 10-year risk between events and nonevents was approximately 8% to 9%, indicating excellent discrimination. Mean calibration, or calibration-in-the-large, was excellent for both studies, with average predicted 10-year risk within one-half of a percent of the observed event rate. An accurate estimate of 10-year CHD risk can be obtained using traditional risk factors and CAC. The MESA risk score, which is available online on the MESA web site for easy use, can be used to aid clinicians when communicating risk to patients and when determining risk-based treatment strategies. Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Zhao, Di; Weng, Chunhua
2011-10-01
In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. Copyright © 2011 Elsevier Inc. All rights reserved.
Zhao, Di; Weng, Chunhua
2011-01-01
In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. PMID:21642013
R Hussein, Nawfal
2018-01-01
Hepatitis B virus (HBV) infection is a public health problem. The lack of information about the seroprevalence and risk factors is an obstacle for preventive public health plans to reduce the burden of viral hepatitis. Therefore, this study was conducted in Iraq, where no studies had been performed to determine the prevalence and risk factors of HBV infection. Blood samples were collected form 438 blood donors attending blood bank in Duhok city. Serum samples were tested for HBV core-antibodies (HBcAb) and HBV surface-antigen (HBsAg) by ELISA. Various risk factors were recorded and multivariate analysis was performed. 5/438 (1.14%) of the subjects were HBsAg positive (HBsAg and HBcAb positive) and 36/438 (8.2%) were HBcAb positive. Hence, 41 cases were exposed to HBV and data analysis was based on that. Univariate analysis showed that there were significant associations between history of illegitimate sexual contact, history of alcohol or history of dental surgeries and HBV exposure (p<0.05 for all). Then, multivariate analysis was conducted to find HBV exposure predictive factors. It was found that history of dental surgery was a predictive factor for exposure to the virus (P=0.03, OR: 2.397). This study suggested that the history of dental surgery was predictive for HBV transmission in Duhok city. Further population-based study is needed to determine HBV risk factors in the society and public health plan based on that should be considered.
Fall risk: the clinical relevance of falls and how to integrate fall risk with fracture risk.
Peeters, G; van Schoor, Natasja M; Lips, Paul
2009-12-01
In old age, 5-10% percent of all falls result in a fracture, and up to 90% of all fractures result from a fall. This article describes the link between fall risk and fracture risk in community-dwelling older persons. Which factors attribute to both the fall risk and the fracture risk? Which falls result in a fracture? Which tools are available to predict falls and fractures? Directions for the use of prediction tools in clinical practice are given. Challenges for future research include further validation of existing prediction tools and evaluation of the cost-effectiveness of treatment after screening.
Seitlinger, Gerd; Ladenhauf, Hannah N; Wierer, Guido
2018-02-01
Patellar instability occurs mainly in young patients and shows a high incidence of concomitant cartilage injuries. Recently there has been a strong attempt to identify risk factors and enhance imaging techniques to detect patients with an increased risk for recurrent patella dislocation.We describe current findings on factors associated with recurrent patella dislocation in the adolescent. Trochlear dysplasia, patellar height, patellar tilt, tibial tuberosity-trochlear groove distance, skeletal maturity, and history of contralateral patellar dislocation are well known significant risk factors for recurrence in adolescent patients. Predictive models to calculate risk of recurrence have been reported recently. The Patellar Instability Severity Score was the first to include demographic and anatomic factors, which is of major value when counseling patients and relatives. Several classification systems to predict the rate of recurrence after primary patella dislocation have been presented over the last years. Anatomic risk factors such as skeletal immaturity, trochlear morphology, patellar height, patellar tilt, and elevated tibial tuberosity-trochlear groove distance have been investigated. However, there is still a lack of knowledge as to how single risk factors or their interaction with each other may contribute.
Metabolic Profiles Predict Adverse Events Following Coronary Artery Bypass Grafting
Shah, Asad A.; Craig, Damian M.; Sebek, Jacqueline K.; Haynes, Carol; Stevens, Robert C.; Muehlbauer, Michael J.; Granger, Christopher B.; Hauser, Elizabeth R.; Newby, L. Kristin; Newgard, Christopher B.; Kraus, William E.; Hughes, G. Chad; Shah, Svati H.
2012-01-01
Objectives Clinical models incompletely predict outcomes following coronary artery bypass grafting. Novel molecular technologies may identify biomarkers to improve risk stratification. We examined whether metabolic profiles can predict adverse events in patients undergoing coronary artery bypass grafting. Methods The study population comprised 478 subjects from the CATHGEN biorepository of patients referred for cardiac catheterization who underwent coronary artery bypass grafting after enrollment. Targeted mass spectrometry-based profiling of 69 metabolites was performed in frozen, fasting plasma samples collected prior to surgery. Principal-components analysis and Cox proportional hazards regression modeling were used to assess the relation between metabolite factor levels and a composite outcome of post-coronary artery bypass grafting myocardial infarction, need for percutaneous coronary intervention, repeat coronary artery bypass grafting, or death. Results Over a mean follow-up of 4.3 ± 2.4 years, 126 subjects (26.4%) suffered an adverse event. Three principal-components analysis-derived factors were significantly associated with adverse outcome in univariable analysis: short-chain dicarboxylacylcarnitines (factor 2, P=0.001); ketone-related metabolites (factor 5, P=0.02); and short-chain acylcarnitines (factor 6, P=0.004). These three factors remained independently predictive of adverse outcome after multivariable adjustment: factor 2 (adjusted hazard ratio 1.23; 95% confidence interval [1.10-1.38]; P<0.001), factor 5 (1.17 [1.01-1.37], P=0.04), and factor 6 (1.14 [1.02-1.27], P=0.03). Conclusions Metabolic profiles are independently associated with adverse outcomes following coronary artery bypass grafting. These profiles may represent novel biomarkers of risk that augment existing tools for risk stratification of coronary artery bypass grafting patients and may elucidate novel biochemical pathways that mediate risk. PMID:22306227
Shao, Hui; Fonseca, Vivian; Stoecker, Charles; Liu, Shuqian; Shi, Lizheng
2018-05-03
There is an urgent need to update diabetes prediction, which has relied on the United Kingdom Prospective Diabetes Study (UKPDS) that dates back to 1970 s' European populations. The objective of this study was to develop a risk engine with multiple risk equations using a recent patient cohort with type 2 diabetes mellitus reflective of the US population. A total of 17 risk equations for predicting diabetes-related microvascular and macrovascular events, hypoglycemia, mortality, and progression of diabetes risk factors were estimated using the data from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (n = 10,251). Internal and external validation processes were used to assess performance of the Building, Relating, Assessing, and Validating Outcomes (BRAVO) risk engine. One-way sensitivity analysis was conducted to examine the impact of risk factors on mortality at the population level. The BRAVO risk engine added several risk factors including severe hypoglycemia and common US racial/ethnicity categories compared with the UKPDS risk engine. The BRAVO risk engine also modeled mortality escalation associated with intensive glycemic control (i.e., glycosylated hemoglobin < 6.5%). External validation showed a good prediction power on 28 endpoints observed from other clinical trials (slope = 1.071, R 2 = 0.86). The BRAVO risk engine for the US diabetes cohort provides an alternative to the UKPDS risk engine. It can be applied to assist clinical and policy decision making such as cost-effective resource allocation in USA.
Bekelis, Kimon; Bakhoum, Samuel F; Desai, Atman; Mackenzie, Todd A; Goodney, Philip; Labropoulos, Nicos
2013-04-01
Accurate knowledge of individualized risks and benefits is crucial to the surgical management of patients undergoing carotid endarterectomy (CEA). Although large randomized trials have determined specific cutoffs for the degree of stenosis, precise delineation of patient-level risks remains a topic of debate, especially in real world practice. We attempted to create a risk factor-based predictive model of outcomes in CEA. We performed a retrospective cohort study involving patients who underwent CEAs from 2005 to 2010 and were registered in the American College of Surgeons National Quality Improvement Project database. Of the 35 698 patients, 20 015 were asymptomatic (56.1%) and 15 683 were symptomatic (43.9%). These patients demonstrated a 1.64% risk of stroke, 0.69% risk of myocardial infarction, and 0.75% risk of death within 30 days after CEA. Multivariate analysis demonstrated that increasing age, male sex, history of chronic obstructive pulmonary disease, myocardial infarction, angina, congestive heart failure, peripheral vascular disease, previous stroke or transient ischemic attack, and dialysis were independent risk factors associated with an increased risk of the combined outcome of postoperative stroke, myocardial infarction, or death. A validated model for outcome prediction based on individual patient characteristics was developed. There was a steep effect of age on the risk of myocardial infarction and death. This national study confirms that that risks of CEA vary dramatically based on patient-level characteristics. Because of limited discrimination, it cannot be used for individual patient risk assessment. However, it can be used as a baseline for improvement and development of more accurate predictive models based on other databases or prospective studies.
Individual risk of cutaneous melanoma in New Zealand: developing a clinical prediction aid.
Sneyd, Mary Jane; Cameron, Claire; Cox, Brian
2014-05-22
New Zealand and Australia have the highest melanoma incidence rates worldwide. In New Zealand, both the incidence and thickness have been increasing. Clinical decisions require accurate risk prediction but a simple list of genetic, phenotypic and behavioural risk factors is inadequate to estimate individual risk as the risk factors for melanoma have complex interactions. In order to offer tailored clinical management strategies, we developed a New Zealand prediction model to estimate individual 5-year absolute risk of melanoma. A population-based case-control study (368 cases and 270 controls) of melanoma risk factors provided estimates of relative risks for fair-skinned New Zealanders aged 20-79 years. Model selection techniques and multivariate logistic regression were used to determine the important predictors. The relative risks for predictors were combined with baseline melanoma incidence rates and non-melanoma mortality rates to calculate individual probabilities of developing melanoma within 5 years. For women, the best model included skin colour, number of moles > =5 mm on the right arm, having a 1st degree relative with large moles, and a personal history of non-melanoma skin cancer (NMSC). The model correctly classified 68% of participants; the C-statistic was 0.74. For men, the best model included age, place of occupation up to age 18 years, number of moles > =5 mm on the right arm, birthplace, and a history of NMSC. The model correctly classified 67% of cases; the C-statistic was 0.71. We have developed the first New Zealand risk prediction model that calculates individual absolute 5-year risk of melanoma. This model will aid physicians to identify individuals at high risk, allowing them to individually target surveillance and other management strategies, and thereby reduce the high melanoma burden in New Zealand.
Dunlop, Malcolm G.; Tenesa, Albert; Farrington, Susan M.; Ballereau, Stephane; Brewster, David H.; Pharoah, Paul DP.; Schafmayer, Clemens; Hampe, Jochen; Völzke, Henry; Chang-Claude, Jenny; Hoffmeister, Michael; Brenner, Hermann; von Holst, Susanna; Picelli, Simone; Lindblom, Annika; Jenkins, Mark A.; Hopper, John L.; Casey, Graham; Duggan, David; Newcomb, Polly; Abulí, Anna; Bessa, Xavier; Ruiz-Ponte, Clara; Castellví-Bel, Sergi; Niittymäki, Iina; Tuupanen, Sari; Karhu, Auli; Aaltonen, Lauri; Zanke, Brent W.; Hudson, Thomas J.; Gallinger, Steven; Barclay, Ella; Martin, Lynn; Gorman, Maggie; Carvajal-Carmona, Luis; Walther, Axel; Kerr, David; Lubbe, Steven; Broderick, Peter; Chandler, Ian; Pittman, Alan; Penegar, Steven; Campbell, Harry; Tomlinson, Ian; Houlston, Richard S.
2016-01-01
Objective Colorectal cancer (CRC) has a substantial heritable component. Common genetic variation has been shown to contribute to CRC risk. In a large, multi-population study, we set out to assess the feasibility of CRC risk prediction using common genetic variant data, combined with other risk factors. We built a risk prediction model and applied it to the Scottish population using available data. Design Nine populations of European descent were studied to develop and validate colorectal cancer risk prediction models. Binary logistic regression was used to assess the combined effect of age, gender, family history (FH) and genotypes at 10 susceptibility loci that individually only modestly influence colorectal cancer risk. Risk models were generated from case-control data incorporating genotypes alone (n=39,266), and in combination with gender, age and family history (n=11,324). Model discriminatory performance was assessed using 10-fold internal cross-validation and externally using 4,187 independent samples. 10-year absolute risk was estimated by modelling genotype and FH with age- and gender-specific population risks. Results Median number of risk alleles was greater in cases than controls (10 vs 9, p<2.2×10−16), confirmed in external validation sets (Sweden p=1.2×10−6, Finland p=2×10−5). Mean per-allele increase in risk was 9% (OR 1.09; 95% CI 1.05–1.13). Discriminative performance was poor across the risk spectrum (area under curve (AUC) for genotypes alone - 0.57; AUC for genotype/age/gender/FH - 0.59). However, modelling genotype data, FH, age and gender with Scottish population data shows the practicalities of identifying a subgroup with >5% predicted 10-year absolute risk. Conclusion We show that genotype data provides additional information that complements age, gender and FH as risk factors. However, individualized genetic risk prediction is not currently feasible. Nonetheless, the modelling exercise suggests public health potential, since it is possible to stratify the population into CRC risk categories, thereby informing targeted prevention and surveillance. PMID:22490517
Quantifying cardiometabolic risk using modifiable non-self-reported risk factors.
Marino, Miguel; Li, Yi; Pencina, Michael J; D'Agostino, Ralph B; Berkman, Lisa F; Buxton, Orfeu M
2014-08-01
Sensitive general cardiometabolic risk assessment tools of modifiable risk factors would be helpful and practical in a range of primary prevention interventions or for preventive health maintenance. To develop and validate a cumulative general cardiometabolic risk score that focuses on non-self-reported modifiable risk factors such as glycosylated hemoglobin (HbA1c) and BMI so as to be sensitive to small changes across a span of major modifiable risk factors, which may not individually cross clinical cut-off points for risk categories. We prospectively followed 2,359 cardiovascular disease (CVD)-free subjects from the Framingham offspring cohort over a 14-year follow-up. Baseline (fifth offspring examination cycle) included HbA1c and cholesterol measurements. Gender-specific Cox proportional hazards models were considered to evaluate the effects of non-self-reported modifiable risk factors (blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking, BMI, and HbA1c) on general CVD risk. We constructed 10-year general cardiometabolic risk score functions and evaluated its predictive performance in 2012-2013. HbA1c was significantly related to general CVD risk. The proposed cardiometabolic general CVD risk model showed good predictive performance as determined by cross-validated discrimination (male C-index=0.703, 95% CI=0.668, 0.734; female C-index=0.762, 95% CI=0.726, 0.801) and calibration (lack-of-fit chi-square=9.05 [p=0.338] and 12.54 [p=0.128] for men and women, respectively). This study presents a risk factor algorithm that provides a convenient and informative way to quantify cardiometabolic risk on the basis of modifiable risk factors that can motivate an individual's commitment to prevention and intervention. Copyright © 2014 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
Quantifying Cardiometabolic Risk Using Modifiable Non–Self-Reported Risk Factors
Marino, Miguel; Li, Yi; Pencina, Michael J.; D’Agostino, Ralph B.; Berkman, Lisa F.; Buxton, Orfeu M.
2014-01-01
Background Sensitive general cardiometabolic risk assessment tools of modifiable risk factors would be helpful and practical in a range of primary prevention interventions or for preventive health maintenance. Purpose To develop and validate a cumulative general cardiometabolic risk score that focuses on non–self-reported modifiable risk factors such as glycosylated hemoglobin (HbA1c) and BMI so as to be sensitive to small changes across a span of major modifiable risk factors, which may not individually cross clinical cut off points for risk categories. Methods We prospectively followed 2,359 cardiovascular disease (CVD)-free subjects from the Framingham offspring cohort over a 14–year follow-up. Baseline (fifth offspring examination cycle) included HbA1c and cholesterol measurements. Gender–specific Cox proportional hazards models were considered to evaluate the effects of non–self-reported modifiable risk factors (blood pressure, total cholesterol, high–density lipoprotein cholesterol, smoking, BMI, and HbA1c) on general CVD risk. We constructed 10–year general cardiometabolic risk score functions and evaluated its predictive performance in 2012–2013. Results HbA1c was significantly related to general CVD risk. The proposed cardiometabolic general CVD risk model showed good predictive performance as determined by cross-validated discrimination (male C-index=0.703, 95% CI=0.668, 0.734; female C-index=0.762, 95% CI=0.726, 0.801) and calibration (lack-of-fit χ2=9.05 [p=0.338] and 12.54 [p=0.128] for men and women, respectively). Conclusions This study presents a risk factor algorithm that provides a convenient and informative way to quantify cardiometabolic risk based on modifiable risk factors that can motivate an individual’s commitment to prevention and intervention. PMID:24951039
Developmental dyslexia: predicting individual risk.
Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J
2015-09-01
Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as 'dyslexic' or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. © 2015 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.
PredictABEL: an R package for the assessment of risk prediction models.
Kundu, Suman; Aulchenko, Yurii S; van Duijn, Cornelia M; Janssens, A Cecile J W
2011-04-01
The rapid identification of genetic markers for multifactorial diseases from genome-wide association studies is fuelling interest in investigating the predictive ability and health care utility of genetic risk models. Various measures are available for the assessment of risk prediction models, each addressing a different aspect of performance and utility. We developed PredictABEL, a package in R that covers descriptive tables, measures and figures that are used in the analysis of risk prediction studies such as measures of model fit, predictive ability and clinical utility, and risk distributions, calibration plot and the receiver operating characteristic plot. Tables and figures are saved as separate files in a user-specified format, which include publication-quality EPS and TIFF formats. All figures are available in a ready-made layout, but they can be customized to the preferences of the user. The package has been developed for the analysis of genetic risk prediction studies, but can also be used for studies that only include non-genetic risk factors. PredictABEL is freely available at the websites of GenABEL ( http://www.genabel.org ) and CRAN ( http://cran.r-project.org/).
Shah, Jai L.; Tandon, Neeraj; Keshavan, Matcheri S.
2016-01-01
Aim Accurate prediction of which individuals will go on to develop psychosis would assist early intervention and prevention paradigms. We sought to review investigations of prospective psychosis prediction based on markers and variables examined in longitudinal familial high-risk (FHR) studies. Methods We performed literature searches in MedLine, PubMed and PsycINFO for articles assessing performance characteristics of predictive clinical tests in FHR studies of psychosis. Studies were included if they reported one or more predictive variables in subjects at FHR for psychosis. We complemented this search strategy with references drawn from articles, reviews, book chapters and monographs. Results Across generations of familial high-risk projects, predictive studies have investigated behavioral, cognitive, psychometric, clinical, neuroimaging, and other markers. Recent analyses have incorporated multivariate and multi-domain approaches to risk ascertainment, although with still generally modest results. Conclusions While a broad range of risk factors has been identified, no individual marker or combination of markers can at this time enable accurate prospective prediction of emerging psychosis for individuals at FHR. We outline the complex and multi-level nature of psychotic illness, the myriad of factors influencing its development, and methodological hurdles to accurate and reliable prediction. Prospects and challenges for future generations of FHR studies are discussed in the context of early detection and intervention strategies. PMID:23693118
2009-01-01
Background Human enterovirus 71 (HEV71) can cause Hand, foot, and mouth disease (HFMD) with neurological complications, which may rapidly progress to fulminant cardiorespiratory failure, and death. Early recognition of children at risk is the key to reduce acute mortality and morbidity. Methods We examined data collected through a prospective clinical study of HFMD conducted between 2000 and 2006 that included 3 distinct outbreaks of HEV71 to identify risk factors associated with neurological involvement in children with HFMD. Results Total duration of fever ≥ 3 days, peak temperature ≥ 38.5°C and history of lethargy were identified as independent risk factors for neurological involvement (evident by CSF pleocytosis) in the analysis of 725 children admitted during the first phase of the study. When they were validated in the second phase of the study, two or more (≥ 2) risk factors were present in 162 (65%) of 250 children with CSF pleocytosis compared with 56 (30%) of 186 children with no CSF pleocytosis (OR 4.27, 95% CI2.79–6.56, p < 0.0001). The usefulness of the three risk factors in identifying children with CSF pleocytosis on hospital admission during the second phase of the study was also tested. Peak temperature ≥ 38.5°C and history of lethargy had the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 28%(48/174), 89%(125/140), 76%(48/63) and 50%(125/251), respectively in predicting CSF pleocytosis in children that were seen within the first 2 days of febrile illness. For those presented on the 3rd or later day of febrile illness, the sensitivity, specificity, PPV and NPV of ≥ 2 risk factors predictive of CSF pleocytosis were 75%(57/76), 59%(27/46), 75%(57/76) and 59%(27/46), respectively. Conclusion Three readily elicited clinical risk factors were identified to help detect children at risk of neurological involvement. These risk factors may serve as a guide to clinicians to decide the need for hospitalization and further investigation, including cerebrospinal fluid examination, and close monitoring for disease progression in children with HFMD. PMID:19152683
In-hospital fall-risk screening in 4,735 geriatric patients from the LUCAS project.
Neumann, L; Hoffmann, V S; Golgert, S; Hasford, J; Von Renteln-Kruse, W
2013-03-01
In-hospital falls in older patients are frequent, but the identification of patients at risk of falling is challenging. Aim of this study was to improve the identification of high-risk patients. Therefore, a simplified screening-tool was developed, validated, and compared to the STRATIFY predictive accuracy. Retrospective analysis of 4,735 patients; evaluation of predictive accuracy of STRATIFY and its single risk factors, as well as age, gender and psychotropic medication; splitting the dataset into a learning and a validation sample for modelling fall-risk screening and independent, temporal validation. Geriatric clinic at an academic teaching hospital in Hamburg, Germany. 4,735 hospitalised patients ≥65 years. Sensitivity, specificity, positive and negative predictive value, Odds Ratios, Youden-Index and the rates of falls and fallers were calculated. There were 10.7% fallers, and the fall rate was 7.9/1,000 hospital days. In the learning sample, mental alteration (OR 2.9), fall history (OR 2.1), and insecure mobility (Barthel-Index items 'transfer' + 'walking' score = 5, 10 or 15) (OR 2.3) had the most strongest association to falls. The LUCAS Fall-Risk Screening uses these risk factors, and patients with ≥2 risk factors contributed to the high-risk group (30.9%). In the validation sample, STRATIFY SENS was 56.8, SPEC 59.6, PPV 13.5 and NPV 92.6 vs. LUCAS Fall-Risk Screening was SENS 46.0, SPEC 71.1, PPV 14.9 and NPV 92.3. Both the STRATIFY and the LUCAS Fall-Risk Screening showed comparable results in defining a high-risk group. Impaired mobility and cognitive status were closely associated to falls. The results do underscore the importance of functional status as essential fall-risk factor in older hospitalised patients.
ERIC Educational Resources Information Center
Morrongiello, Barbara A.; Matheis, Shawn
2004-01-01
This study examined the contribution of cognitive and emotion-based factors in predicting school-age children's risk-taking decisions when the social-situational context did, and did not, pressure for risk-taking. Using drawings of play situations that depicted three possible paths of travel that varied in injury risk and pitted convenience…
ERIC Educational Resources Information Center
Roberts, Beverly A.; Der, Geoff; Deary, Ian J.; Batty, G. David
2009-01-01
Higher cognitive function is associated with faster choice reaction time (CRT), and both are associated with a reduced risk of mortality from all-causes and cardiovascular disease (CVD). However, comparison of the predictive capacity of CRT, an emerging risk factor, with that for established "classic" risk factors for mortality, such as…
Emura, Takeshi; Nakatochi, Masahiro; Matsui, Shigeyuki; Michimae, Hirofumi; Rondeau, Virginie
2017-01-01
Developing a personalized risk prediction model of death is fundamental for improving patient care and touches on the realm of personalized medicine. The increasing availability of genomic information and large-scale meta-analytic data sets for clinicians has motivated the extension of traditional survival prediction based on the Cox proportional hazards model. The aim of our paper is to develop a personalized risk prediction formula for death according to genetic factors and dynamic tumour progression status based on meta-analytic data. To this end, we extend the existing joint frailty-copula model to a model allowing for high-dimensional genetic factors. In addition, we propose a dynamic prediction formula to predict death given tumour progression events possibly occurring after treatment or surgery. For clinical use, we implement the computation software of the prediction formula in the joint.Cox R package. We also develop a tool to validate the performance of the prediction formula by assessing the prediction error. We illustrate the method with the meta-analysis of individual patient data on ovarian cancer patients.
Molecular epidemiology, and possible real-world applications in breast cancer.
Ito, Hidemi; Matsuo, Keitaro
2016-01-01
Gene-environment interaction, a key idea in molecular epidemiology, has enabled the development of personalized medicine. This concept includes personalized prevention. While genome-wide association studies have identified a number of genetic susceptibility loci in breast cancer risk, however, the application of this knowledge to practical prevention is still underway. Here, we briefly review the history of molecular epidemiology and its progress in breast cancer epidemiology. We then introduce our experience with the trial combination of GWAS-identified loci and well-established lifestyle and reproductive risk factors in the risk prediction of breast cancer. Finally, we report our exploration of the cumulative risk of breast cancer based on this risk prediction model as a potential tool for individual risk communication, including genetic risk factors and gene-environment interaction with obesity.
Ormel, J; Oldehinkel, A J; Ferdinand, R F; Hartman, C A; De Winter, A F; Veenstra, R; Vollebergh, W; Minderaa, R B; Buitelaar, J K; Verhulst, F C
2005-12-01
We investigated the links between familial loading, preadolescent temperament, and internalizing and externalizing problems in adolescence, hereby distinguishing effects on maladjustment in general versus dimension-specific effects on either internalizing or externalizing problems. In a population-based sample of 2230 preadolescents (10-11 years) familial loading (parental lifetime psychopathology) and offspring temperament were assessed at baseline by parent report, and offspring psychopathology at 2.5-years follow-up by self-report, teacher report and parent report. We used purified measures of temperament and psychopathology and partialled out shared variance between internalizing and externalizing problems. Familial loading of internalizing psychopathology predicted offspring internalizing but not externalizing problems, whereas familial loading of externalizing psychopathology predicted offspring externalizing but not internalizing problems. Both familial loadings were associated with Frustration, low Effortful Control, and Fear. Frustration acted as a general risk factor predicting severity of maladjustment; low Effortful Control and Fear acted as dimension-specific risk factors that predicted a particular type of psychopathology; whereas Shyness, High-Intensity Pleasure, and Affiliation acted as direction markers that steered the conditional probability of internalizing versus externalizing problems, in the event of maladjustment. Temperament traits mediated one-third of the association between familial loading and psychopathology. Findings were robust across different composite measures of psychopathology, and applied to girls as well as boys. With regard to familial loading and temperament, it is important to distinguish general risk factors (Frustration) from dimension-specific risk factors (familial loadings, Effortful Control, Fear), and direction markers that act as pathoplastic factors (Shyness, High-Intensity Pleasure, Affiliation) from both types of risk factors. About one-third of familial loading effects on psychopathology in early adolescence are mediated by temperament.
Dufour, A B; Roberts, B; Broe, K E; Kiel, D P; Bouxsein, M L; Hannan, M T
2012-02-01
We examined the relation between a biomechanical measure, factor-of-risk, and hip fracture risk in 1,100 men and women from the Framingham Study and found that it predicted hip fracture (men, ORs of 1.8; women, 1.2-1.4). Alternative methods of predicting hip fracture are needed since 50% of adults who fracture do not have osteoporosis by bone mineral density (BMD) measurements. One method, factor-of-risk (Φ), computes the ratio of force on the hip in a fall to femoral strength. We examined the relation between Φ and hip fracture in 1,100 subjects from the Framingham Study with measured hip BMD, along with weight, height, and age, collected in 1988-1989. We estimated both peak and attenuated force applied to the hip in a sideways fall from standing height, where attenuated force incorporated cushioning effects of trochanteric soft tissue. Femoral strength was estimated from femoral neck BMD, using cadaveric femoral strength data. Sex-specific, age-adjusted survival models were used to calculate hazard ratios (HR) and 95% confidence intervals for the relation between Φ (peak), Φ (attenuated), and their components with hip fracture. In 425 men and 675 women (mean age, 76 years), 136 hip fractures occurred over median follow-up of 11.3 years. Factor-of-risk, Φ, was associated with increased age-adjusted risk for hip fracture. One standard deviation increase in Φ (peak) and Φ (attenuated) was associated with HR of 1.88 and 1.78 in men and 1.23 and 1.41 in women, respectively. Examining components of Φ, in women, we found fall force and soft tissue thickness were predictive of hip fracture independent of femoral strength (was estimated from BMD). Thus, both Φ (peak) and Φ (attenuated) predict hip fracture in men and women. These findings suggest additional studies of Φ predicting hip fracture using direct measurements of trochanteric soft tissue.
Ganga, G M D; Esposto, K F; Braatz, D
2012-01-01
The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.
Hou, Xuwei; Jiang, Yu; Wang, Ningfu; Shen, Yun; Wang, Xiaoyan; Zhong, Yigang; Xu, Peng; Zhou, Liang
2015-01-01
Abstract The role of diagonal ear lobe crease (DELC) in coronary artery disease (CAD) diagnosis and prognosis remains controversial. In this study, we aimed to assess the combined effect of DELC with other conventional risk factors in the diagnosis and prognosis of CAD in Chinese patients who underwent angiography and coronary stent implantation. The study consisted of 956 consecutive patients who underwent angiography. The DELC was identified as no DELC, unilateral, and bilateral DELC. The conventional risk factors for CAD were recorded. Our dada showed that the overall presence of DELC is associated with CAD risk. Stratification analyses revealed that the diagnostic value of DELC was mostly significant in those with >4 risk factors. Also in patients with >4 risk factors, the presence of bilateral DELC remains to be associated with higher hs-CRP level, higher severity of CAD, and higher possibility of developing major adverse cardiac events after successful percutaneous coronary intervention (PCI). Our study confirmed the relation of DELC with CAD in Chinese patients; more importantly, our data suggest the combination of DELC and CAD risk factors will help to predict the incidence of CAD and may predict the prognosis after successfully PCI. PMID:26131833
Risk factors for body dissatisfaction in adolescent boys and girls: a prospective study.
Presnell, Katherine; Bearman, Sarah Kate; Stice, Eric
2004-12-01
Despite evidence that body dissatisfaction predicts the onset of eating pathology and depression, few prospective studies have investigated predictors of body dissatisfaction. We examined risk factors for body dissatisfaction using prospective data from 531 adolescent boys and girls. Elevations in body mass, negative affect, and perceived pressure to be thin from peers, but not thin-ideal internalization, social support deficits, or perceived pressure to be thin from family, dating partners, or media, predicted increases in body dissatisfaction. Gender moderated the effect of body mass on body dissatisfaction and revealed a significant quadratic component for boys, but not girls. Gender also moderated negative affect. Results support the assertion that certain sociocultural, biologic, and interpersonal factors increase the risk for body dissatisfaction, but differ for boys and girls. Results provided little support for other accepted risk factors for body dissatisfaction. Copyright 2004 by Wiley Periodicals, Inc.
Cahir, Caitriona; Barron, Thomas I; Sharp, Linda; Bennett, Kathleen
2017-03-01
To investigate whether demographic, clinical and treatment-related risk factors known at treatment initiation can be used to reliably predict future hormonal therapy non-persistence in women with breast cancer, and to inform intervention development. Women with stage I-III breast cancer diagnosed 2000-2012 and prescribed hormonal therapy were identified from the National Cancer Registry Ireland (NCRI) and linked to pharmacy claims data from Ireland's Primary Care Reimbursement Services (PCRS). Non-persistence was defined as a treatment gap of ≥180 days within 5 years of initiation. Seventeen demographic, clinical and treatment-related risk factors, identified from a systematic review, were abstracted from the NCRI-PCRS dataset. Multivariate binomial models were used to estimate relative risks (RR) and risk differences (RD) for associations between risk factors and non-persistence. Calibration and discriminative performance of the models were assessed. The analysis was repeated for early non-persistence (<1 year of initiation). Within 5 years of treatment initiation 680 women (19.9%) were non-persistent. Women aged <50 years (adjusted RR 1.41, 95% CI 1.16-1.70) and those prescribed antidepressants (RR 1.22, 95% CI 1.04-1.45) had increased risk of non-persistence. Married women (RR 0.82 95% CI 0.71-0.94) and those with prior medication use (RR 0.62 95% CI 0.51-0.75) had reduced risk of non-persistence. The area under the receiver-operating characteristic (ROC) curve for non-persistence was 0.61. Findings were similar for early non-persistence. The risk prediction model did not discriminate well between women at higher and lower risk of non-persistence at treatment initiation. Future studies should consider other factors, such as psychological characteristics and experience of side-effects.
Clinical Risk Factors for In-Hospital Adverse Cardiovascular Events After Acute Drug Overdose
Manini, Alex F.; Hoffman, Robert S.; Stimmel, Barry; Vlahov, David
2015-01-01
Objectives It was recently demonstrated that adverse cardiovascular events (ACVE) complicate a high proportion of hospitalizations for patients with acute drug overdoses. The aim of this study was to derive independent clinical risk factors for ACVE in patients with acute drug overdoses. Methods This prospective cohort study was conducted over 3 years at two urban university hospitals. Patients were adults with acute drug overdoses enrolled from the ED. In-hospital ACVE was defined as any of myocardial injury, shock, ventricular dysrhythmia, or cardiac arrest. Results There were 1,562 patients meeting inclusion/exclusion criteria (mean age, 41.8 years; female, 46%; suicidal, 38%). ACVE occurred in 82 (5.7%) patients (myocardial injury, 61; shock, 37; dysrhythmia, 23; cardiac arrests, 22) and there were 18 (1.2%) deaths. On univariate analysis, ACVE risk increased with age, lower serum bicarbonate, prolonged QTc interval, prior cardiac disease, and altered mental status. In a multivariable model adjusting for these factors as well as patient sex and hospital site, independent predictors were: QTc > 500 msec (3.8% prevalence, odds ratio [OR] 27.6), bicarbonate < 20 mEql/L (5.4% prevalence, OR 4.4), and prior cardiac disease (7.1% prevalence, OR 9.5). The derived prediction rule had 51.6% sensitivity, 93.7% specificity, and 97.1% negative predictive value; while presence of two or more risk factors had 90.9% positive predictive value. Conclusions The authors derived independent clinical risk factors for ACVE in patients with acute drug overdose, which should be validated in future studies as a prediction rule in distinct patient populations and clinical settings. PMID:25903997
Rajaei, Samira; Dabbagh, Ali
2012-01-01
ABSTRACT Nowadays, coronary artery bypass grafting (CABG) is considered to be one of the most common surgical procedures. This procedure has been the main topic in many clinical research studies, which have assessed the effect of the procedure on patients’ outcomes. Like other surgical procedures, this procedure is also accompanied by a number of unwanted complications, including those of the respiratory system. Since the respiratory system plays an integral role in defining the clinical outcome of patients, improvements in studies that can assess and predict clinical outcomes of the respiratory system, assume greater importance. There are a number of predictive models which can assess patients in the preoperative period and introduce a number of risk factors, which could be considered as prognostic factors for patients undergoing CABG. The respiratory system is among the clinical systems that are assessed in many prediction scoring systems. This review assesses the main studies which have evaluated the possible risk factors for postoperative respiratory mortality and morbidity, in patients undergoing CABG. PMID:24223339
Witt, Katrina; Lichtenstein, Paul; Fazel, Seena
2015-01-01
Background Violence risk assessment in schizophrenia relies heavily on criminal history factors. Aims To investigate which criminal history factors are most strongly associated with violent crime in schizophrenia. Method A total of 13 806 individuals (8891 men and 4915 women) with two or more hospital admissions for schizophrenia were followed up for violent convictions. Multivariate hazard ratios for 15 criminal history factors included in different risk assessment tools were calculated. The incremental predictive validity of these factors was estimated using tests of discrimination, calibration and reclassification. Results Over a mean follow-up of 12.0 years, 17.3% of men (n = 1535) and 5.7% of women (n = 281) were convicted of a violent offence. Criminal history factors most strongly associated with subsequent violence for both men and women were a previous conviction for a violent offence; for assault, illegal threats and/or intimidation; and imprisonment. However, only a previous conviction for a violent offence was associated with incremental predictive validity in both genders following adjustment for young age and comorbid substance use disorder. Conclusions Clinical and actuarial approaches to assess violence risk can be improved if included risk factors are tested using multiple measures of performance. PMID:25657352
Witt, Katrina; Lichtenstein, Paul; Fazel, Seena
2015-05-01
Violence risk assessment in schizophrenia relies heavily on criminal history factors. To investigate which criminal history factors are most strongly associated with violent crime in schizophrenia. A total of 13 806 individuals (8891 men and 4915 women) with two or more hospital admissions for schizophrenia were followed up for violent convictions. Multivariate hazard ratios for 15 criminal history factors included in different risk assessment tools were calculated. The incremental predictive validity of these factors was estimated using tests of discrimination, calibration and reclassification. Over a mean follow-up of 12.0 years, 17.3% of men (n = 1535) and 5.7% of women (n = 281) were convicted of a violent offence. Criminal history factors most strongly associated with subsequent violence for both men and women were a previous conviction for a violent offence; for assault, illegal threats and/or intimidation; and imprisonment. However, only a previous conviction for a violent offence was associated with incremental predictive validity in both genders following adjustment for young age and comorbid substance use disorder. Clinical and actuarial approaches to assess violence risk can be improved if included risk factors are tested using multiple measures of performance. © The Royal College of Psychiatrists 2015.
A Revised Framingham Stroke Risk Profile to Reflect Temporal Trends
Dufouil, Carole; Beiser, Alexa; McLure, Leslie A.; Wolf, Philip A.; Tzourio, Christophe; Howard, Virginia J; Westwood, Andrew J.; Himali, Jayandra J.; Sullivan, Lisa; Aparicio, Hugo J.; Kelly-Hayes, Margaret; Ritchie, Karen; Kase, Carlos S.; Pikula, Aleksandra; Romero, Jose R.; D’Agostino, Ralph B.; Samieri, Cécilia; Vasan, Ramachandran S.; Chêne, Genevieve; Howard, George; Seshadri, Sudha
2017-01-01
Background Age-adjusted stroke incidence has decreased over the past 50 years, likely due to changes in the prevalence and impact of various stroke risk factors. An updated version of the Framingham Stroke Risk Profile (FSRP) might better predict current risks in the Framingham Heart Study (FHS) and other cohorts. We compared the accuracy of the standard (Old), and of a revised (New) version of the FSRP in predicting the risk of all-stroke and ischemic stroke, and validated this new FSRP in two external cohorts, the 3 Cities (3C) and REGARDS studies. Methods We computed the old FSRP as originally described, and a new model that used the most recent epoch-specific risk factors' prevalence and hazard-ratios for persons ≥ 55 years and for the subsample ≥ 65 years (to match the age range in REGARDS and 3C studies respectively), and compared the efficacy of these models in predicting 5- and 10-year stroke risks. Results The new FSRP was a better predictor of current stroke risks in all three samples than the old FSRP (Calibration chi-squares of new/old FSRP: in men 64.0/12.1, 59.4/30.6 and 20.7/12.5; in women 42.5/4.1, 115.4/90.3 and 9.8/6.5 in FHS, REGARDS and 3C, respectively). In the REGARDS, the new FSRP was a better predictor among whites compared to blacks. Conclusions A more contemporaneous, new FSRP better predicts current risks in 3 large community samples and could serve as the basis for examining geographic and racial differences in stroke risk and the incremental diagnostic utility of novel stroke risk factors. PMID:28159800
Revised Framingham Stroke Risk Profile to Reflect Temporal Trends.
Dufouil, Carole; Beiser, Alexa; McLure, Leslie A; Wolf, Philip A; Tzourio, Christophe; Howard, Virginia J; Westwood, Andrew J; Himali, Jayandra J; Sullivan, Lisa; Aparicio, Hugo J; Kelly-Hayes, Margaret; Ritchie, Karen; Kase, Carlos S; Pikula, Aleksandra; Romero, Jose R; D'Agostino, Ralph B; Samieri, Cécilia; Vasan, Ramachandran S; Chêne, Genevieve; Howard, George; Seshadri, Sudha
2017-03-21
Age-adjusted stroke incidence has decreased over the past 50 years, likely as a result of changes in the prevalence and impact of various stroke risk factors. An updated version of the Framingham Stroke Risk Profile (FSRP) might better predict current risks in the FHS (Framingham Heart Study) and other cohorts. We compared the accuracy of the standard (old) and of a revised (new) version of the FSRP in predicting the risk of all-stroke and ischemic stroke and validated this new FSRP in 2 external cohorts, the 3C (3 Cities) and REGARDS (Reasons for Geographic and Racial Differences in Stroke) studies. We computed the old FSRP as originally described and a new model that used the most recent epoch-specific risk factor prevalence and hazard ratios for individuals ≥55 years of age and for the subsample ≥65 years of age (to match the age range in REGARDS and 3C studies, respectively) and compared the efficacy of these models in predicting 5- and 10-year stroke risks. The new FSRP was a better predictor of current stroke risks in all 3 samples than the old FSRP (calibration χ 2 of new/old FSRP: in men: 64.0/12.1, 59.4/30.6, and 20.7/12.5; in women: 42.5/4.1, 115.4/90.3, and 9.8/6.5 in FHS, REGARDS, and 3C, respectively). In the REGARDS, the new FSRP was a better predictor among whites compared with blacks. A more contemporaneous, new FSRP better predicts current risks in 3 large community samples and could serve as the basis for examining geographic and racial differences in stroke risk and the incremental diagnostic utility of novel stroke risk factors. © 2017 American Heart Association, Inc.
Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn
2014-01-01
Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate. PMID:25325356
Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn
2014-10-16
Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate.
Adolescent Alcohol Use: Protective and Predictive Parent, Peer, and Self-Related Factors
Donaldson, Candice D.; Crano, William D.
2018-01-01
Adolescent alcohol use has been linked with a multitude of problems and a trajectory predictive of problematic use in adulthood. Thus, targeting factors that enhance early prevention efforts is vital. The current study highlights variables that mitigate or predict alcohol use and heavy episodic drinking. Using Monitoring the Future (MTF) data, multiple path analytic models revealed links between parental involvement and alcohol abstinence and initiation. Parental involvement predicted enhanced self-esteem and less self-derogation and was negatively associated with peer alcohol norms for each MTF grade sampled, with stronger associations for 8th and 10th graders than 12th graders. For younger groups, self-esteem predicted increased perceptions of alcohol risk and reduced drinking. Self-derogation was associated with peers’ pro-alcohol norms, which was linked to lower risk perceptions, lower personal disapproval of use, and increased drinking. Peer influence had a stronger association with consumption for 8th and 10th graders, whereas 12th graders’ drinking was related to personal factors of alcohol risk perception and disapproval. In all grades, general alcohol use had a strong connection to heavy episodic drinking within the past 2 weeks. Across-grade variations in association of parent, peer, and personal factors suggest the desirability of tailored interventions focused on specific factors for each grade level, with the overall goal of attenuating adolescent alcohol use. PMID:27562038
Geographic profiling to assess the risk of rare plant poaching in natural areas
Young, J.A.; Van Manen, F.T.; Thatcher, C.A.
2011-01-01
We demonstrate the use of an expert-assisted spatial model to examine geographic factors influencing the poaching risk of a rare plant (American ginseng, Panax quinquefolius L.) in Shenandoah National Park, Virginia, USA. Following principles of the analytic hierarchy process (AHP), we identified a hierarchy of 11 geographic factors deemed important to poaching risk and requested law enforcement personnel of the National Park Service to rank those factors in a series of pair-wise comparisons. We used those comparisons to determine statistical weightings of each factor and combined them into a spatial model predicting poaching risk. We tested the model using 69 locations of previous poaching incidents recorded by law enforcement personnel. These locations occurred more frequently in areas predicted by the model to have a higher risk of poaching than random locations. The results of our study can be used to evaluate resource protection strategies and to target law enforcement activities. ?? Springer Science+Business Media, LLC (outside the USA) 2011.
Kasch, Helge; Qerama, Erisela; Kongsted, Alice; Bach, Flemming W; Bendix, Tom; Jensen, Troels S
2011-12-01
One-year prospective study of 141 acute whiplash patients (WLP) and 40 acute ankle-injured controls. This study investigates a priori determined potential risk factors to develop a risk assessment tool, for which the expediency was examined. The whiplash-associated disorders (WAD) grading system that emerged from The Quebec Task-Force-on-Whiplash has been of limited value for predicting work-related recovery and for explaining biopsychosocial disability after whiplash and new predictive factors, for example, risk criteria that comprehensively differentiate acute WLP in a biopsychosocial manner are needed. Consecutively, 141 acute WLP and 40 ankle-injured recruited from emergency units were examined after 1 week, 1, 3, 6, and 12 months obtaining neck/head visual analog scale score, number of nonpainful complaints, epidemiological, social, psychological data and neurological examination, active neck mobility, and furthermore muscle tenderness and pain response, and strength and duration of neck muscles. Risk factors derived (reduced cervical range of motion, intense neck pain/headache, multiple nonpain complaints) were applied in a risk assessment score and divided into seven risk strata. A receiver operating characteristics curve for the Risk Assessment Score and 1-year work disability showed an area of 0.90. Risk strata and number of sick days showed a log-linear relationship. In stratum 1 full recovery was encountered, but for high-risk patients in stratum 6 only 50% and 7 only 20% had returned to work after 1 year (P < 5.4 × 10). Strength measures, psychophysical pain measurements, and psychological and social data (reported elsewhere) showed significant relation to risk strata. The Risk Assessment score is suggested as a valuable tool for grading WLP early after injury. It has reasonable screening power for encountering work disability and reflects the biopsychosocial nature of whiplash injuries.
Chi, Chih-Lin; Zeng, Wenjun; Oh, Wonsuk; Borson, Soo; Lenskaia, Tatiana; Shen, Xinpeng; Tonellato, Peter J
2017-12-01
Prediction of onset and progression of cognitive decline and dementia is important both for understanding the underlying disease processes and for planning health care for populations at risk. Predictors identified in research studies are typically accessed at one point in time. In this manuscript, we argue that an accurate model for predicting cognitive status over relatively long periods requires inclusion of time-varying components that are sequentially assessed at multiple time points (e.g., in multiple follow-up visits). We developed a pilot model to test the feasibility of using either estimated or observed risk factors to predict cognitive status. We developed two models, the first using a sequential estimation of risk factors originally obtained from 8 years prior, then improved by optimization. This model can predict how cognition will change over relatively long time periods. The second model uses observed rather than estimated time-varying risk factors and, as expected, results in better prediction. This model can predict when newly observed data are acquired in a follow-up visit. Performances of both models that are evaluated in10-fold cross-validation and various patient subgroups show supporting evidence for these pilot models. Each model consists of multiple base prediction units (BPUs), which were trained using the same set of data. The difference in usage and function between the two models is the source of input data: either estimated or observed data. In the next step of model refinement, we plan to integrate the two types of data together to flexibly predict dementia status and changes over time, when some time-varying predictors are measured only once and others are measured repeatedly. Computationally, both data provide upper and lower bounds for predictive performance. Copyright © 2017 Elsevier Inc. All rights reserved.
Genetic Predisposition to Ischemic Stroke
Kamatani, Yoichiro; Takahashi, Atsushi; Hata, Jun; Furukawa, Ryohei; Shiwa, Yuh; Yamaji, Taiki; Hara, Megumi; Tanno, Kozo; Ohmomo, Hideki; Ono, Kanako; Takashima, Naoyuki; Matsuda, Koichi; Wakai, Kenji; Sawada, Norie; Iwasaki, Motoki; Yamagishi, Kazumasa; Ago, Tetsuro; Ninomiya, Toshiharu; Fukushima, Akimune; Hozawa, Atsushi; Minegishi, Naoko; Satoh, Mamoru; Endo, Ryujin; Sasaki, Makoto; Sakata, Kiyomi; Kobayashi, Seiichiro; Ogasawara, Kuniaki; Nakamura, Motoyuki; Hitomi, Jiro; Kita, Yoshikuni; Tanaka, Keitaro; Iso, Hiroyasu; Kitazono, Takanari; Kubo, Michiaki; Tanaka, Hideo; Tsugane, Shoichiro; Kiyohara, Yutaka; Yamamoto, Masayuki; Sobue, Kenji; Shimizu, Atsushi
2017-01-01
Background and Purpose— The prediction of genetic predispositions to ischemic stroke (IS) may allow the identification of individuals at elevated risk and thereby prevent IS in clinical practice. Previously developed weighted multilocus genetic risk scores showed limited predictive ability for IS. Here, we investigated the predictive ability of a newer method, polygenic risk score (polyGRS), based on the idea that a few strong signals, as well as several weaker signals, can be collectively informative to determine IS risk. Methods— We genotyped 13 214 Japanese individuals with IS and 26 470 controls (derivation samples) and generated both multilocus genetic risk scores and polyGRS, using the same derivation data set. The predictive abilities of each scoring system were then assessed using 2 independent sets of Japanese samples (KyushuU and JPJM data sets). Results— In both validation data sets, polyGRS was shown to be significantly associated with IS, but weighted multilocus genetic risk scores was not. Comparing the highest with the lowest polyGRS quintile, the odds ratios for IS were 1.75 (95% confidence interval, 1.33–2.31) and 1.99 (95% confidence interval, 1.19–3.33) in the KyushuU and JPJM samples, respectively. Using the KyushuU samples, the addition of polyGRS to a nongenetic risk model resulted in a significant improvement of the predictive ability (net reclassification improvement=0.151; P<0.001). Conclusions— The polyGRS was shown to be superior to weighted multilocus genetic risk scores as an IS prediction model. Thus, together with the nongenetic risk factors, polyGRS will provide valuable information for individual risk assessment and management of modifiable risk factors. PMID:28034966
Risk Factors of Attempted Suicide in Bipolar Disorder
ERIC Educational Resources Information Center
Cassidy, Frederick
2011-01-01
Suicide rates of bipolar patients are among the highest of any psychiatric disorder, and improved identification of risk factors for attempted and completed suicide translates into improved clinical outcome. Factors that may be predictive of suicidality in an exclusively bipolar population are examined. White race, family suicide history, and…
Zhou, Jinzhe; Zhou, Yanbing; Cao, Shougen; Li, Shikuan; Wang, Hao; Niu, Zhaojian; Chen, Dong; Wang, Dongsheng; Lv, Liang; Zhang, Jian; Li, Yu; Jiao, Xuelong; Tan, Xiaojie; Zhang, Jianli; Wang, Haibo; Zhang, Bingyuan; Lu, Yun; Sun, Zhenqing
2016-01-01
Reporting of surgical complications is common, but few provide information about the severity and estimate risk factors of complications. If have, but lack of specificity. We retrospectively analyzed data on 2795 gastric cancer patients underwent surgical procedure at the Affiliated Hospital of Qingdao University between June 2007 and June 2012, established multivariate logistic regression model to predictive risk factors related to the postoperative complications according to the Clavien-Dindo classification system. Twenty-four out of 86 variables were identified statistically significant in univariate logistic regression analysis, 11 significant variables entered multivariate analysis were employed to produce the risk model. Liver cirrhosis, diabetes mellitus, Child classification, invasion of neighboring organs, combined resection, introperative transfusion, Billroth II anastomosis of reconstruction, malnutrition, surgical volume of surgeons, operating time and age were independent risk factors for postoperative complications after gastrectomy. Based on logistic regression equation, p=Exp∑BiXi / (1+Exp∑BiXi), multivariate logistic regression predictive model that calculated the risk of postoperative morbidity was developed, p = 1/(1 + e((4.810-1.287X1-0.504X2-0.500X3-0.474X4-0.405X5-0.318X6-0.316X7-0.305X8-0.278X9-0.255X10-0.138X11))). The accuracy, sensitivity and specificity of the model to predict the postoperative complications were 86.7%, 76.2% and 88.6%, respectively. This risk model based on Clavien-Dindo grading severity of complications system and logistic regression analysis can predict severe morbidity specific to an individual patient's risk factors, estimate patients' risks and benefits of gastric surgery as an accurate decision-making tool and may serve as a template for the development of risk models for other surgical groups.
Schonberg, Mara A; Li, Vicky W; Eliassen, A Heather; Davis, Roger B; LaCroix, Andrea Z; McCarthy, Ellen P; Rosner, Bernard A; Chlebowski, Rowan T; Hankinson, Susan E; Marcantonio, Edward R; Ngo, Long H
2016-12-01
Accurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death. We included 73,066 women who completed the 2004 Nurses' Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors) and 7 risk factors for non-breast cancer death (comorbidities, functional dependency) and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women's Health Initiative Extension Study (WHI-ES; all were ≥55 years and followed for 5 years). Within 5 years, 1.8 % of NHS participants were diagnosed with breast cancer (vs. 2.0 % in WHI-ES, p = 0.02), and 6.6 % experienced non-breast cancer death (vs. 5.2 % in WHI-ES, p < 0.001). Using a model selection procedure which incorporated the Akaike Information Criterion, c-statistic, statistical significance, and clinical judgement, our final model included 9 breast cancer risk factors, 5 comorbidities, functional dependency, and mammography use. The model's c-statistic was 0.61 (95 % CI [0.60-0.63]) in NHS and 0.57 (0.55-0.58) in WHI-ES. On average, our model under predicted breast cancer in WHI-ES (E/O 0.92 [0.88-0.97]). We developed a novel prediction model that factors in postmenopausal women's individualized competing risks of non-breast cancer death when estimating breast cancer risk.
Schonberg, Mara A.; Li, Vicky W.; Eliassen, A. Heather; Davis, Roger B.; LaCroix, Andrea Z.; McCarthy, Ellen P.; Rosner, Bernard A.; Chlebowski, Rowan T.; Hankinson, Susan E.; Marcantonio, Edward R.; Ngo, Long H.
2016-01-01
Purpose Accurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death. Methods We included 73,066 women who completed the 2004 Nurses’ Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors), 7 risk factors for non-breast cancer death (comorbidities, functional dependency), and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women’s Health Initiative Extension Study (WHI-ES; all were ≥55 years and followed for 5 years). Results Within 5 years, 1.8% of NHS participants were diagnosed with breast cancer (vs. 2.0% in WHI-ES, p=0.02) and 6.6% experienced non-breast cancer death (vs. 5.2% in WHI-ES, p<0.001). Using a model selection procedure which incorporated the Akaike Information Criterion, c-statistic, statistical significance, and clinical judgement, our final model included 9 breast cancer risk factors, 5 comorbidities, functional dependency, and mammography use. The model’s c-statistic was 0.61 (95% CI [0.60–0.63]) in NHS and 0.57 (0.55–0.58) in WHI-ES. On average our model under predicted breast cancer in WHI-ES (E/O 0.92 [0.88–0.97]). Conclusions We developed a novel prediction model that factors in postmenopausal women’s individualized competing risks of non-breast cancer death when estimating breast cancer risk. PMID:27770283
Colorectal Cancer Risk Assessment Tool
... 11/12/2014 Risk Calculator About the Tool Colorectal Cancer Risk Factors Download SAS and Gauss Code Page ... Rectal Cancer: Prevention, Genetics, Causes Tests to Detect Colorectal Cancer and Polyps Cancer Risk Prediction Resources Update November ...
Schultze, Daniel; Hillebrand, Norbert; Hinz, Ulf; Büchler, Markus W.; Schemmer, Peter
2014-01-01
Background and Aims Liver transplantation is the only curative treatment for end-stage liver disease. While waiting list mortality can be predicted by the MELD-score, reliable scoring systems for the postoperative period do not exist. This study's objective was to identify risk factors that contribute to postoperative mortality. Methods Between December 2006 and March 2011, 429 patients underwent liver transplantation in our department. Risk factors for postoperative mortality in 266 consecutive liver transplantations were identified using univariate and multivariate analyses. Patients who were <18 years, HU-listings, and split-, living related, combined or re-transplantations were excluded from the analysis. The correlation between number of risk factors and mortality was analyzed. Results A labMELD ≥20, female sex, coronary heart disease, donor risk index >1.5 and donor Na+>145 mmol/L were identified to be independent predictive factors for postoperative mortality. With increasing number of these risk-factors, postoperative 90-day and 1-year mortality increased (0–1: 0 and 0%; 2: 2.9 and 17.4%; 3: 5.6 and 16.8%; 4: 22.2 and 33.3%; 5–6: 60.9 and 66.2%). Conclusions In this analysis, a simple score was derived that adequately identified patients at risk after liver transplantation. Opening a discussion on the inclusion of these parameters in the process of organ allocation may be a worthwhile venture. PMID:24905210
Brenton, Ashley; Richeimer, Steven; Sharma, Maneesh; Lee, Chee; Kantorovich, Svetlana; Blanchard, John; Meshkin, Brian
2017-01-01
Opioid abuse in chronic pain patients is a major public health issue, with rapidly increasing addiction rates and deaths from unintentional overdose more than quadrupling since 1999. This study seeks to determine the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm incorporating phenotypic risk factors and neuroscience-associated single-nucleotide polymorphisms (SNPs). The Proove Opioid Risk (POR) algorithm determines the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm incorporating phenotypic risk factors and neuroscience-associated SNPs. In a validation study with 258 subjects with diagnosed opioid use disorder (OUD) and 650 controls who reported using opioids, the POR successfully categorized patients at high and moderate risks of opioid misuse or abuse with 95.7% sensitivity. Regardless of changes in the prevalence of opioid misuse or abuse, the sensitivity of POR remained >95%. The POR correctly stratifies patients into low-, moderate-, and high-risk categories to appropriately identify patients at need for additional guidance, monitoring, or treatment changes.
Dodani, Sunita
2008-01-01
Background: Coronary artery disease (CAD) is the leading cause of mortality and morbidity in the United States (US), and South Asian immigrants (SAIs) have a higher risk of CAD compared to Caucasians. Traditional risk factors may not completely explain high risk, and some of the unknown risk factors need to be explored. This short review is mainly focused on the possible role of dysfunctional high-density lipoprotein (HDL) in causing CAD and presents an overview of available literature on dysfunctional HDL. Discussion: The conventional risk factors, insulin resistance parameters, and metabolic syndrome, although important in predicting CAD risk, may not sufficiently predict risk in SAIs. HDL has antioxidant, antiinflammatory, and antithrombotic properties that contribute to its function as an antiatherogenic agent. Recent Caucasian studies have shown HDL is not only ineffective as an antioxidant but, paradoxically, appears to be prooxidant, and has been found to be associated with CAD. Several causes have been hypothesized for HDL to become dysfunctional, including Apo lipoprotein A-I (Apo A-I) polymorphisms. New risk factors and markers like dysfunctional HDL and genetic polymorphisms may be associated with CAD. Conclusions: More research is required in SAIs to explore associations with CAD and to enhance early detection and prevention of CAD in this high risk group. PMID:19183743
Reveles, Kelly R; Mortensen, Eric M; Koeller, Jim M; Lawson, Kenneth A; Pugh, Mary Jo V; Rumbellow, Sarah A; Argamany, Jacqueline R; Frei, Christopher R
2018-03-01
Prior studies have identified risk factors for recurrent Clostridium difficile infection (CDI), but few studies have integrated these factors into a clinical prediction rule that can aid clinical decision-making. The objectives of this study were to derive and validate a CDI recurrence prediction rule to identify patients at risk for first recurrence in a national cohort of veterans. Retrospective cohort study. Veterans Affairs Informatics and Computing Infrastructure. A total of 22,615 adult Veterans Health Administration beneficiaries with first-episode CDI between October 1, 2002, and September 30, 2014; of these patients, 7538 were assigned to the derivation cohort and 15,077 to the validation cohort. A 60-day CDI recurrence prediction rule was created in a derivation cohort using backward logistic regression. Those variables significant at p<0.01 were assigned an integer score proportional to the regression coefficient. The model was then validated in the derivation cohort and a separate validation cohort. Patients were then split into three risk categories, and rates of recurrence were described for each category. The CDI recurrence prediction rule included the following predictor variables with their respective point values: prior third- and fourth-generation cephalosporins (1 point), prior proton pump inhibitors (1 point), prior antidiarrheals (1 point), nonsevere CDI (2 points), and community-onset CDI (3 points). In the derivation cohort, the 60-day CDI recurrence risk for each score ranged from 7.5% (0 points) to 57.9% (8 points). The risk score was strongly correlated with recurrence (R 2 = 0.94). Patients were split into low-risk (0-2 points), medium-risk (3-5 points), and high-risk (6-8 points) classes and had the following recurrence rates: 8.9%, 20.2%, and 35.0%, respectively. Findings were similar in the validation cohort. Several CDI and patient-specific factors were independently associated with 60-day CDI recurrence risk. When integrated into a clinical prediction rule, higher risk scores and risk classes were strongly correlated with CDI recurrence. This clinical prediction rule can be used by providers to identify patients at high risk for CDI recurrence and help guide preventive strategy decisions, while accounting for clinical judgment. © 2018 Pharmacotherapy Publications, Inc.
Sartor, Carolyn E; Kranzler, Henry R; Gelernter, Joel
2014-02-01
A number of demographic factors, psychiatric disorders, and childhood risk factors have been associated with cocaine dependence (CD) and opioid dependence (OD), but little is known about their relevance to the rate at which dependence develops. Identification of the subpopulations at elevated risk for rapid development of dependence and the risk factors that accelerate the course of dependence is an important public health goal. Data were derived from cocaine dependent (n=6333) and opioid dependent (n=3513) participants in a multi-site study of substance dependence. Mean age was approximately 40 and 40% of participants were women; 51.9% of cocaine dependent participants and 29.5% of opioid dependent participants self-identified as Black/African-American. The time from first use to dependence was calculated for each substance and a range of demographic, psychiatric, and childhood risk factors were entered into ordinal logistic regression models to predict the (categorical) transition time to CD and OD. In both the cocaine and opioid models, conduct disorder and childhood physical abuse predicted rapid development of dependence and alcohol and nicotine dependence diagnoses were associated with slower progression to CD or OD. Blacks/African Americans were at greater risk than European Americans to progress rapidly to OD. Only a subset of factors known to be associated with CD and OD predicted the rate at which dependence developed. Nearly all were common to cocaine and opioids, suggesting that sources of influence on the timing of transitions to dependence are shared across the two substances. © 2013.
McDonough, Tiffani L; Paolicchi, Juliann M; Heier, Linda A; Das, Nikkan; Engel, Murray; Perlman, Jeffrey M; Grinspan, Zachary M
2017-06-01
Epilepsy outcomes after therapeutic hypothermia for neonates with hypoxic-ischemic encephalopathy are understudied. The authors used multivariable logistic regression to predict epilepsy in neonates after selective head cooling. Sensitivity analyses used magnetic resonance imaging (MRI) and electroencephalogram (EEG) interpretations by different clinicians. Fifty neonates had 2-year follow-up. Nine developed epilepsy. Predictors included pH ≤6.8 on day of birth (adjusted odds ratio [OR] 19 [95% confidence interval (CI) 1-371]), burst suppression on EEG on day 4 (8.2 [1.3-59]), and MRI deep gray matter injury (OR 33 [2.4-460]). These factors stratify neonates into low (0-1 factors; 3% [0%-14%] risk), medium (2 factors; 56% [21%-86%] risk), and high-risk groups (3 factors; 100% [29%-100%] risk) for epilepsy. The stratification was robust to varying clinical interpretations of the MRI and EEG. Neonates with hypoxic-ischemic encephalopathy who undergo selective head cooling appear at risk of epilepsy if they have 2 to 3 identified factors. If validated, this rule may help counsel families and identify children for close clinical follow-up.
NASA Astrophysics Data System (ADS)
Blauhut, V.; Stahl, K.; Stagge, J. H.; Tallaksen, L. M.; De Stefano, L.; Vogt, J.
2015-12-01
Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work (1) tests the capability of commonly applied hazard indicators and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and (2) combines information on past drought impacts, drought hazard indicators, and vulnerability factors into estimates of drought risk at the pan-European scale. This "hybrid approach" bridges the gap between traditional vulnerability assessment and probabilistic impact forecast in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro region specific sensitivities of hazard indicators, with the Standardised Precipitation Evapotranspiration Index for a twelve month aggregation period (SPEI-12) as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictor, with information about landuse and water resources as best vulnerability-based predictors. (3) The application of the "hybrid approach" revealed strong regional (NUTS combo level) and sector specific differences in drought risk across Europe. The majority of best predictor combinations rely on a combination of SPEI for shorter and longer aggregation periods, and a combination of information on landuse and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, current practice of drought indicators selection for specific application, and drought risk assessment.
The risk factors of laryngeal pathology in Korean adults using a decision tree model.
Byeon, Haewon
2015-01-01
The purpose of this study was to identify risk factors affecting laryngeal pathology in the Korean population and to evaluate the derived prediction model. Cross-sectional study. Data were drawn from the 2008 Korea National Health and Nutritional Examination Survey. The subjects were 3135 persons (1508 male and 2114 female) aged 19 years and older living in the community. The independent variables were age, sex, occupation, smoking, alcohol drinking, and self-reported voice problems. A decision tree analysis was done to identify risk factors for predicting a model of laryngeal pathology. The significant risk factors of laryngeal pathology were age, gender, occupation, smoking, and self-reported voice problem in decision tree model. Four significant paths were identified in the decision tree model for the prediction of laryngeal pathology. Those identified as high risk groups for laryngeal pathology included those who self-reported a voice problem, those who were males in their 50s who did not recognize a voice problem, those who were not economically active males in their 40s, and male workers aged 19 and over and under 50 or 60 and over who currently smoked. The results of this study suggest that individual risk factors, such as age, sex, occupation, health behavior, and self-reported voice problem, affect the onset of laryngeal pathology in a complex manner. Based on the results of this study, early management of the high-risk groups is needed for the prevention of laryngeal pathology. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.
Cheong, Kee C; Ghazali, Sumarni M; Hock, Lim K; Yusoff, Ahmad F; Selvarajah, Sharmini; Haniff, Jamaiyah; Zainuddin, Ahmad Ali; Ying, Chan Y; Lin, Khor G; Rahman, Jamalludin A; Shahar, Suzana; Mustafa, Amal N
2014-01-01
Previous studies have proposed the lower waist circumference (WC) cutoffs be used for defining abdominal obesity in Asian populations. To determine the optimal cut-offs of waist circumference (WC) in predicting cardiovascular (CV) risk factors in the multi-ethnic Malaysian population. We analysed data from 32,703 respondents (14,980 men and 17,723 women) aged 18 years and above who participated in the Third National Health and Morbidity Survey in 2006. Gender-specific logistic regression analyses were used to examine associations between WC and three CV risk factors (diabetes mellitus, hypertension, and hypercholesterolemia). The Receiver Operating Characteristic (ROC) curves were used to determine the cut-off values of WC with optimum sensitivity and specificity for detecting these CV risk factors. The odds ratio for having diabetes mellitus, hypertension, and hypercholesterolemia, or at least one of these risks, increased significantly as the WC cut-off point increased. Optimal WC cut-off values for predicting the presence of diabetes mellitus, hypertension, hypercholesterolemia and at least one of the three CV risk factors varied from 81.4 to 85.5 cm for men and 79.8 to 80.7 cm for women. Our findings indicate that WC cut-offs of 81 cm for men and 80 cm for women are appropriate for defining abdominal obesity and for recommendation to undergo cardiovascular risk screening and weight management in the Malaysian adult population. © 2014 Asian Oceanian Association for the Study of Obesity . Published by Elsevier Ltd. All rights reserved.
Jiang, Xuejuan; Varma, Rohit; Wu, Shuang; Torres, Mina; Azen, Stanley P; Francis, Brian A.; Chopra, Vikas; Nguyen, Betsy Bao-Thu
2012-01-01
Objective To determine which baseline socio-demographic, lifestyle, anthropometric, clinical, and ocular risk factors predict the development of open-angle glaucoma (OAG) in an adult population. Design A population-based, prospective cohort study. Participants A total of 3,772 self-identified Latinos aged 40 years and older from Los Angeles, California who were free of OAG at baseline. Methods Participants from the Los Angeles Latino Eye Study had standardized study visits at baseline and 4-year follow-up with structured interviews and a comprehensive ophthalmologic examination. OAG was defined as the presence of an open angle and a glaucomatous visual field abnormality and/or evidence of glaucomatous optic nerve damage in at least one eye. Multivariate logistic regression with stepwise selection was performed to determine which potential baseline risk factors independently predict the development of OAG. Main Outcome Measure Odds ratios for various risk factors. Results Over the 4-year follow-up, 87 participants developed OAG. The baseline risk factors that predict the development of OAG include: older age (odds ratio [OR] per decade, 2.19; 95% confidence intervals [CI], 1.74-2.75; P<0.001), higher intraocular pressure (OR per mmHg, 1.18; 95% CI, 1.10-1.26; P<0.001), longer axial length (OR per mm, 1.48; 95% CI, 1.22-1.80; P<0.001), thinner central cornea (OR per 40 μm thinner, 1.30; 95% CI, 1.00-1.70; P=0.050) higher waist to hip ratio (OR per 0.05 higher, 1.21; 95% CI, 1.05-1.39; P=0.007) and lack of vision insurance (OR, 2.08; 95% CI, 1.26-3.41; P=0.004). Conclusions Despite a mean baseline IOP of 14 mmHg in Latinos, higher intraocular pressure is an important risk factor for developing OAG. Biometric measures suggestive of less structural support such as longer axial length and thin CCT were identified as important risk factors. Lack of health insurance reduces access to eye care and increases the burden of OAG by reducing the likelihood of early detection and treatment of OAG. PMID:22796305
A simplified donor risk index for predicting outcome after deceased donor kidney transplantation.
Watson, Christopher J E; Johnson, Rachel J; Birch, Rhiannon; Collett, Dave; Bradley, J Andrew
2012-02-15
We sought to determine the deceased donor factors associated with outcome after kidney transplantation and to develop a clinically applicable Kidney Donor Risk Index. Data from the UK Transplant Registry on 7620 adult recipients of adult deceased donor kidney transplants between 2000 and 2007 inclusive were analyzed. Donor factors potentially influencing transplant outcome were investigated using Cox regression, adjusting for significant recipient and transplant factors. A United Kingdom Kidney Donor Risk Index was derived from the model and validated. Donor age was the most significant factor predicting poor transplant outcome (hazard ratio for 18-39 and 60+ years relative to 40-59 years was 0.78 and 1.49, respectively, P<0.001). A history of donor hypertension was also associated with increased risk (hazard ratio 1.30, P=0.001), and increased donor body weight, longer hospital stay before death, and use of adrenaline were also significantly associated with poorer outcomes up to 3 years posttransplant. Other donor factors including donation after circulatory death, history of cardiothoracic disease, diabetes history, and terminal creatinine were not significant. A donor risk index based on the five significant donor factors was derived and confirmed to be prognostic of outcome in a validation cohort (concordance statistic 0.62). An index developed in the United States by Rao et al., Transplantation 2009; 88: 231-236, included 15 factors and gave a concordance statistic of 0.63 in the UK context, suggesting that our much simpler model has equivalent predictive ability. A Kidney Donor Risk Index based on five donor variables provides a clinically useful tool that may help with organ allocation and informed consent.
Skeem, J L; Mulvey, E P
2001-06-01
Although psychopathy is recognized as a relatively strong risk factor for violence among inmates and mentally disordered offenders, few studies have examined the extent to which its predictive power generalizes to civil psychiatric samples. Using data on 1,136 patients from the MacArthur Violence Risk Assessment project, this study examined whether the 2 scales that underlie the Psychopathy Checklist: Screening Version (PCL:SV) measure a unique personality construct that predicts violence among civil patients. The results indicate that the PCL:SV is a relatively strong predictor of violence. The PCL:SV's predictive power is substantially reduced, but remains significant, after controlling for a host of covariates that reflect antisocial behavior and personality disorders other than psychopathy. However, the predictive power of the PCL:SV is not based on its assessment of the core traits of psychopathy, as traditionally construed. Implications for the 2-factor model that underlies the PCL measures and for risk assessment practice are discussed.
Kusaka, Mamoru; Kubota, Yusuke; Sasaki, Hitomi; Fukami, Naohiko; Fujita, Tamio; Hirose, Yuichi; Takahashi, Hiroshi; Kenmochi, Takashi; Shiroki, Ryoichi; Hoshinaga, Kiyotaka
2016-04-01
Kidneys procured from the deceased hold great potential for expanding the donor pool. The aims of the present study were to investigate the post-transplant outcomes of renal allografts recovered from donors after cardiac death, to identify risk factors affecting the renal prognosis and to compare the long-term survival from donors after cardiac death according to the number of risk factors shown by expanded criteria donors. A total of 443 grafts recovered using an in situ regional cooling technique from 1983 to 2011 were assessed. To assess the combined predictive value of the significant expanded criteria donor risk criteria, the patients were divided into three groups: those with no expanded criteria donor risk factors (no risk), one expanded criteria donor risk factor (single-risk) and two or more expanded criteria donor risk factors (multiple-risk). Among the donor factors, age ≥50 years, hypertension, maximum serum creatinine level ≥1.5 mg/dL and a warm ischemia time ≥30 min were identified as independent predictors of long-term graft failure on multivariate analysis. Regarding the expanded criteria donors criteria for marginal donors, cerebrovascular disease, hypertension and maximum serum creatinine level ≥1.5 mg/dL were identified as significant predictors on univariate analysis. The single- and multiple-risk groups showed 2.01- and 2.40-fold higher risks of graft loss, respectively. Renal grafts recovered from donors after cardiac death donors have a good renal function with an excellent long-term graft survival. However, an increased number of expanded criteria donors risk factors increase the risk of graft loss. © 2016 The Japanese Urological Association.
Hoffmann, Udo; Massaro, Joseph M; D'Agostino, Ralph B; Kathiresan, Sekar; Fox, Caroline S; O'Donnell, Christopher J
2016-02-22
We determined whether vascular and valvular calcification predicted incident major coronary heart disease, cardiovascular disease (CVD), and all-cause mortality independent of Framingham risk factors in the community-based Framingham Heart Study. Coronary artery calcium (CAC), thoracic and abdominal aortic calcium, and mitral or aortic valve calcium were measured by cardiac computed tomography in participants free of CVD. Participants were followed for a median of 8 years. Multivariate Cox proportional hazards models were used to determine association of CAC, thoracic and abdominal aortic calcium, and mitral and aortic valve calcium with end points. Improvement in discrimination beyond risk factors was tested via the C-statistic and net reclassification index. In this cohort of 3486 participants (mean age 50±10 years; 51% female), CAC was most strongly associated with major coronary heart disease, followed by major CVD, and all-cause mortality independent of Framingham risk factors. Among noncoronary calcifications, mitral valve calcium was associated with major CVD and all-cause mortality independent of Framingham risk factors and CAC. CAC significantly improved discriminatory value beyond risk factors for coronary heart disease (area under the curve 0.78-0.82; net reclassification index 32%, 95% CI 11-53) but not for CVD. CAC accurately reclassified 85% of the 261 patients who were at intermediate (5-10%) 10-year risk for coronary heart disease based on Framingham risk factors to either low risk (n=172; no events observed) or high risk (n=53; observed event rate 8%). CAC improves discrimination and risk reclassification for major coronary heart disease and CVD beyond risk factors in asymptomatic community-dwelling persons and accurately reclassifies two-thirds of the intermediate-risk population. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.
Ma, Hon Ming; Ip, Margaret; Woo, Jean; Hui, David S C
2014-05-01
Health care-associated pneumonia (HCAP) and drug-resistant bacterial pneumonia may not share identical risk factors. We have shown that bronchiectasis, recent hospitalization and severe pneumonia (confusion, blood urea level, respiratory rate, low blood pressure and 65 year old (CURB-65) score ≥ 3) were independent predictors of pneumonia caused by potentially drug-resistant (PDR) pathogens. This study aimed to develop and validate a clinical risk score for predicting drug-resistant bacterial pneumonia in older patients. We derived a risk score by assigning a weighting to each of these risk factors as follows: 14, bronchiectasis; 5, recent hospitalization; 2, severe pneumonia. A 0.5 point was defined for the presence of other risk factors for HCAP. We compared the areas under the receiver-operating characteristics curve (AUROC) of our risk score and the HCAP definition in predicting PDR pathogens in two cohorts of older patients hospitalized with non-nosocomial pneumonia. The derivation and validation cohorts consisted of 354 and 96 patients with bacterial pneumonia, respectively. PDR pathogens were isolated in 48 and 21 patients in the derivation and validation cohorts, respectively. The AUROCs of our risk score and the HCAP definition were 0.751 and 0.650, respectively, in the derivation cohort, and were 0.782 and 0.671, respectively, in the validation cohort. The differences between our risk score and the HCAP definition reached statistical significance. A score ≥ 2.5 had the best balance between sensitivity and specificity. Our risk score outperformed the HCAP definition to predict pneumonia caused by PDR pathogens. A history of bronchiectasis or recent hospitalization is the major indication of starting empirical broad-spectrum antibiotics. © 2014 Asian Pacific Society of Respirology.
Simón, Luis; Afonin, Alexandr; López-Díez, Lucía Isabel; González-Miguel, Javier; Morchón, Rodrigo; Carretón, Elena; Montoya-Alonso, José Alberto; Kartashev, Vladimir; Simón, Fernando
2014-03-01
Zoonotic filarioses caused by Dirofilaria immitis and Dirofilaria repens are transmitted by culicid mosquitoes. Therefore Dirofilaria transmission depends on climatic factors like temperature and humidity. In spite of the dry climate of most of the Spanish territory, there are extensive irrigated crops areas providing moist habitats favourable for mosquito breeding. A GIS model to predict the risk of Dirofilaria transmission in Spain, based on temperatures and rainfall data as well as in the distribution of irrigated crops areas, is constructed. The model predicts that potential risk of Dirofilaria transmission exists in all the Spanish territory. Highest transmission risk exists in several areas of Andalucía, Extremadura, Castilla-La Mancha, Murcia, Valencia, Aragón and Cataluña, where moderate/high temperatures coincide with extensive irrigated crops. High risk in Balearic Islands and in some points of Canary Islands, is also predicted. The lowest risk is predicted in Northern cold and scarcely or non-irrigated dry Southeastern areas. The existence of irrigations locally increases transmission risk in low rainfall areas of the Spanish territory. The model can contribute to implement rational preventive therapy guidelines in accordance with the transmission characteristics of each local area. Moreover, the use of humidity-related factors could be of interest in future predictions to be performed in countries with similar environmental characteristics. Copyright © 2014 Elsevier B.V. All rights reserved.
Jang, Eun Jin; Park, ByeongJu; Kim, Tae-Young; Shin, Soon-Ae
2016-01-01
Background Asian-specific prediction models for estimating individual risk of osteoporotic fractures are rare. We developed a Korean fracture risk prediction model using clinical risk factors and assessed validity of the final model. Methods A total of 718,306 Korean men and women aged 50–90 years were followed for 7 years in a national system-based cohort study. In total, 50% of the subjects were assigned randomly to the development dataset and 50% were assigned to the validation dataset. Clinical risk factors for osteoporotic fracture were assessed at the biennial health check. Data on osteoporotic fractures during the follow-up period were identified by ICD-10 codes and the nationwide database of the National Health Insurance Service (NHIS). Results During the follow-up period, 19,840 osteoporotic fractures were reported (4,889 in men and 14,951 in women) in the development dataset. The assessment tool called the Korean Fracture Risk Score (KFRS) is comprised of a set of nine variables, including age, body mass index, recent fragility fracture, current smoking, high alcohol intake, lack of regular exercise, recent use of oral glucocorticoid, rheumatoid arthritis, and other causes of secondary osteoporosis. The KFRS predicted osteoporotic fractures over the 7 years. This score was validated using an independent dataset. A close relationship with overall fracture rate was observed when we compared the mean predicted scores after applying the KFRS with the observed risks after 7 years within each 10th of predicted risk. Conclusion We developed a Korean specific prediction model for osteoporotic fractures. The KFRS was able to predict risk of fracture in the primary population without bone mineral density testing and is therefore suitable for use in both clinical setting and self-assessment. The website is available at http://www.nhis.or.kr. PMID:27399597
Kim, Ha Young; Jang, Eun Jin; Park, ByeongJu; Kim, Tae-Young; Shin, Soon-Ae; Ha, Yong-Chan; Jang, Sunmee
2016-01-01
Asian-specific prediction models for estimating individual risk of osteoporotic fractures are rare. We developed a Korean fracture risk prediction model using clinical risk factors and assessed validity of the final model. A total of 718,306 Korean men and women aged 50-90 years were followed for 7 years in a national system-based cohort study. In total, 50% of the subjects were assigned randomly to the development dataset and 50% were assigned to the validation dataset. Clinical risk factors for osteoporotic fracture were assessed at the biennial health check. Data on osteoporotic fractures during the follow-up period were identified by ICD-10 codes and the nationwide database of the National Health Insurance Service (NHIS). During the follow-up period, 19,840 osteoporotic fractures were reported (4,889 in men and 14,951 in women) in the development dataset. The assessment tool called the Korean Fracture Risk Score (KFRS) is comprised of a set of nine variables, including age, body mass index, recent fragility fracture, current smoking, high alcohol intake, lack of regular exercise, recent use of oral glucocorticoid, rheumatoid arthritis, and other causes of secondary osteoporosis. The KFRS predicted osteoporotic fractures over the 7 years. This score was validated using an independent dataset. A close relationship with overall fracture rate was observed when we compared the mean predicted scores after applying the KFRS with the observed risks after 7 years within each 10th of predicted risk. We developed a Korean specific prediction model for osteoporotic fractures. The KFRS was able to predict risk of fracture in the primary population without bone mineral density testing and is therefore suitable for use in both clinical setting and self-assessment. The website is available at http://www.nhis.or.kr.
Easton, Jonathan F; Stephens, Christopher R; Angelova, Maia
2014-11-01
Data mining and knowledge discovery as an approach to examining medical data can limit some of the inherent bias in the hypothesis assumptions that can be found in traditional clinical data analysis. In this paper we illustrate the benefits of a data mining inspired approach to statistically analysing a bespoke data set, the academic multicentre randomised control trial, U.K Glucose Insulin in Stroke Trial (GIST-UK), with a view to discovering new insights distinct from the original hypotheses of the trial. We consider post-stroke mortality prediction as a function of days since stroke onset, showing that the time scales that best characterise changes in mortality risk are most naturally defined by examination of the mortality curve. We show that certain risk factors differentiate between very short term and intermediate term mortality. In particular, we show that age is highly relevant for intermediate term risk but not for very short or short term mortality. We suggest that this is due to the concept of frailty. Other risk factors are highlighted across a range of variable types including socio-demographics, past medical histories and admission medication. Using the most statistically significant risk factors we build predictive classification models for very short term and short/intermediate term mortality. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.
Oguoma, Victor M; Nwose, Ezekiel U; Ulasi, Ifeoma I; Akintunde, Adeseye A; Chukwukelu, Ekene E; Bwititi, Phillip T; Richards, Ross S; Skinner, Timothy C
2017-01-06
Diabetes is a risk factor for cardiovascular diseases (CVDs) and there are reports of increasing prevalence of prediabetes in Nigeria. This study therefore characterised CVDs risk factors in subjects with impaired fasting glucose (IFG) and diabetes. Data from 4 population-based cross-sectional studies on 2447 apparently healthy individuals from 18 - 89 years were analysed. Anthropometric, blood pressure and biochemical parameters were collected and classified. Individuals with IFG (prediabetes) and diabetes were merged each for positive cases of dyslipidaemia, high blood pressure (HBP) or obesity. Optimal Discriminant and Hierarchical Optimal Classification Tree Analysis (HO-CTA) were employed. Overall prevalence of IFG and diabetes were 5.8% (CI: 4.9 - 6.7%) and 3.1% (CI: 2.4 - 3.8%), respectively. IFG co-morbidity with dyslipidaemia (5.0%; CI: 4.1 - 5.8%) was the highest followed by overweight/obese (3.1%; CI: 2.5 - 3.8%) and HBP (1.8%; CI: 1.3 - 2.4%). The predicted age of IFG or diabetes and their co-morbidity with other CVD risk factors were between 40 - 45 years. Elevated blood level of total cholesterol was the most predictive co-morbid risk factor among IFG and diabetes subjects. Hypertriglyceridaemia was an important risk factor among IFG-normocholesterolaemic-overweight/obese individuals. The higher prevalence of co-morbidity of CVD risk factors with IFG than in diabetes plus the similar age of co-morbidity between IFG and diabetes highlights the need for risk assessment models for prediabetes and education of individuals at risk about factors that mitigate development of diabetes and CVDs.
Predicting Acute and Persistent Neuropathy Associated with Oxaliplatin
Alejandro, Linh; Behrendt, Carolyn E.; Chen, Kim; Openshaw, Harry; Shibata, Stephen
2014-01-01
Objectives We sought to predict oxaliplatin-associated peripheral neuropathy during modified FOLFOX6 (mFOLFOX6) therapy. Methods In a 50% female sample, patients with previously untreated, primary or recurrent colorectal cancer were followed through a first course of mFOLFOX6 with oxaliplatin 85 mg/m2 every 2 weeks. Accounting for correlation among a subject's cycles, logistic regression estimated per-cycle risk of acute (under 14 days) and persistent (14 days or more) neuropathy. Proportional hazards regression predicted time to persistent neuropathy. Results Among mFOLFOX6 recipients (n=50, age 58.9 +10.1 years), 36% received concomitant bevacizumab. Of total cycles, 94.2% (422/448) were evaluable. Most (84%) subjects reported neuropathy at least once: 74% reported acute and 48% reported persistent symptoms. On multivariate analysis, risk factors shared by acute and persistent neuropathy were body-surface area >2.0, acute neuropathy in a past cycle, and lower body weight. In addition, risk of acute neuropathy decreased with age (adjusted for renal function and winter season), while risk of persistent neuropathy increased with cumulative dose of oxaliplatin and persistent neuropathy in a past cycle. Concomitant bevacizumab was not a risk factor when administered in Stage IV disease but was associated with persistent neuropathy when administered experimentally in Stage III. Females had no increased risk of either form of neuropathy. After 3 cycles, weight, body-surface area, and prior acute neuropathy predicted time to persistent neuropathy. Conclusions Routinely available clinical factors predict acute and persistent neuropathy associated with oxaliplatin. When validated, the proposed prognostic score for persistent neuropathy can help clinicians counsel patients about chemotherapy. PMID:22547012
Jostins, Luke; Levine, Adam P; Barrett, Jeffrey C
2013-01-01
A central focus of complex disease genetics after genome-wide association studies (GWAS) is to identify low frequency and rare risk variants, which may account for an important fraction of disease heritability unexplained by GWAS. A profusion of studies using next-generation sequencing are seeking such risk alleles. We describe how already-known complex trait loci (largely from GWAS) can be used to guide the design of these new studies by selecting cases, controls, or families who are most likely to harbor undiscovered risk alleles. We show that genetic risk prediction can select unrelated cases from large cohorts who are enriched for unknown risk factors, or multiply-affected families that are more likely to harbor high-penetrance risk alleles. We derive the frequency of an undiscovered risk allele in selected cases and controls, and show how this relates to the variance explained by the risk score, the disease prevalence and the population frequency of the risk allele. We also describe a new method for informing the design of sequencing studies using genetic risk prediction in large partially-genotyped families using an extension of the Inside-Outside algorithm for inference on trees. We explore several study design scenarios using both simulated and real data, and show that in many cases genetic risk prediction can provide significant increases in power to detect low-frequency and rare risk alleles. The same approach can also be used to aid discovery of non-genetic risk factors, suggesting possible future utility of genetic risk prediction in conventional epidemiology. Software implementing the methods in this paper is available in the R package Mangrove.
Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.
Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C
2014-03-01
To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
Risk factors for eating disorder symptoms at 12 years of age: A 6-year longitudinal cohort study.
Evans, Elizabeth H; Adamson, Ashley J; Basterfield, Laura; Le Couteur, Ann; Reilly, Jessica K; Reilly, John J; Parkinson, Kathryn N
2017-01-01
Eating disorders pose risks to health and wellbeing in young adolescents, but prospective studies of risk factors are scarce and this has impeded prevention efforts. This longitudinal study aimed to examine risk factors for eating disorder symptoms in a population-based birth cohort of young adolescents at 12 years. Participants from the Gateshead Millennium Study birth cohort (n = 516; 262 girls and 254 boys) completed self-report questionnaire measures of eating disorder symptoms and putative risk factors at age 7 years, 9 years and 12 years, including dietary restraint, depressive symptoms and body dissatisfaction. Body mass index (BMI) was also measured at each age. Within-time correlates of eating disorder symptoms at 12 years of age were greater body dissatisfaction for both sexes and, for girls only, higher depressive symptoms. For both sexes, higher eating disorder symptoms at 9 years old significantly predicted higher eating disorder symptoms at 12 years old. Dietary restraint at 7 years old predicted boys' eating disorder symptoms at age 12, but not girls'. Factors that did not predict eating disorder symptoms at 12 years of age were BMI (any age), girls' dietary restraint at 7 years and body dissatisfaction at 7 and 9 years of age for both sexes. In this population-based study, different patterns of predictors and correlates of eating disorder symptoms were found for girls and boys. Body dissatisfaction, a purported risk factor for eating disorder symptoms in young adolescents, developed concurrently with eating disorder symptoms rather than preceding them. However, restraint at age 7 and eating disorder symptoms at age 9 years did predict 12-year eating disorder symptoms. Overall, our findings suggest that efforts to prevent disordered eating might beneficially focus on preadolescent populations. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Couder, Florence; Massardier, Jérôme; You, Benoît; Abbas, Fatima; Hajri, Touria; Lotz, Jean-Pierre; Schott, Anne-Marie; Golfier, François
2016-07-01
Patients with 2000 FIGO low-risk gestational trophoblastic neoplasia are commonly treated with single-agent chemotherapy. Methotrexate is widely used in this indication in Europe. Analysis of relapse after treatment and identification of factors associated with relapse would help understand their potential impacts on 2000 FIGO score evolution and chemotherapy management of gestational trophoblastic neoplasia patients. This retrospective study analyzes the predictive factors of relapse in low-risk gestational trophoblastic neoplasia patients whose hormone chorionic gonadotropin (hCG) normalized with methotrexate alone. Between 1999 and 2014, 993 patients with gestational trophoblastic neoplasia were identified in the French Trophoblastic Disease Reference Center database, of which 465 were low-risk patients whose hCG normalized with methotrexate alone. Using univariate and multivariate analysis we identified significant predictive factors for relapse after methotrexate. The Kaplan-Meier method was used to plot the outcome of patients. The 5-year recurrence rate of low-risk gestational trophoblastic neoplasia patients whose hCG normalized with methotrexate alone was 5.7% (confidence interval [IC], 3.86-8.46). Univariate analysis identified an antecedent pregnancy resulting in a delivery (HR = 5.96; 95% CI, 1.40-25.4, P = .016), a number of methotrexate courses superior to 5 courses (5-8 courses vs 1-4: HR = 6.19; 95% CI, 1.43-26.8, P = .015; 9 courses and more vs 1-4: HR = 6.80; 95% CI, 1.32-35.1, P = .022), and hCG normalization delay centered to the mean as predictive factors of recurrence (HR = 1.27; 95% CI, 1.09-1.49, P = .003). Multivariate analysis confirmed the type of antecedent pregnancy and the number of methotrexate courses as independent predictive factors of recurrence. A low-risk gestational trophoblastic neoplasia arising after a normal delivery had an 8.66 times higher relapse risk than that of a postmole gestational trophoblastic neoplasia (95% CI, 1.98-37.9], P = .0042). A patient who received 5-8 courses of methotrexate had a 6.7 times higher relapse risk than a patient who received 1-4 courses (95% CI, 1.54-29.2, P = .011). A patient who received 9 courses or more had an 8.1 times higher relapse risk than a patient who received 1-4 courses of methotrexate (95% CI, 1.54-42.6, P = .014). Low-risk gestational trophoblastic neoplasia following a delivery and patients who need more than 4 courses of methotrexate to normalization are at a higher risk of relapse than other low-risk patients. Allotting a higher score to the "antecedent pregnancy" FIGO item should be considered for postdelivery gestational trophoblastic neoplasia. Further analysis of the need for consolidation courses is warranted. Copyright © 2016 Elsevier Inc. All rights reserved.
Violent Recidivism: A Long-Time Follow-Up Study of Mentally Disordered Offenders
Nilsson, Thomas; Wallinius, Märta; Gustavson, Christina; Anckarsäter, Henrik; Kerekes, Nóra
2011-01-01
Background In this prospective study, mentally disordered perpetrators of severe violent and/or sexual crimes were followed through official registers for 59 (range 8 to 73) months. The relapse rate in criminality was assessed, compared between offenders sentenced to prison versus forensic psychiatric care, and the predictive ability of various risk factors (criminological, clinical, and of structured assessment instruments) was investigated. Method One hundred perpetrators were consecutively assessed between 1998 and 2001 by a clinical battery of established instruments covering DSM-IV diagnoses, psychosocial background factors, and structured assessment instruments (HCR-20, PCL-R, and life-time aggression (LHA)). Follow-up data was collected from official registers for: (i) recidivistic crimes, (ii) crimes during ongoing sanction. Results Twenty subjects relapsed in violent criminality during ongoing sanctions (n = 6) or after discharge/parole (n = 14). Individuals in forensic psychiatric care spent significantly more time at liberty after discharge compared to those in prison, but showed significantly fewer relapses. Criminological (age at first conviction), and clinical (conduct disorder and substance abuse/dependence) risk factors, as well as scores on structured assessment instruments, were moderately associated with violent recidivism. Logistic regression analyses showed that the predictive ability of criminological risk factors versus clinical risk factors combined with scores from assessment instruments was comparable, with each set of variables managing to correctly classify about 80% of all individuals, but the only predictors that remained significant in multiple models were criminological (age at first conviction, and a history of substance abuse among primary relatives). Conclusions Only one in five relapsed into serious criminality, with significantly more relapses among subjects sentenced to prison as compared to forensic psychiatric care. Criminological risk factors tended to be the best predictors of violent relapses, while few synergies were seen when the risk factors were combined. Overall, the predictive validity of common risk factors for violent criminality was rather weak. PMID:22022445
Hotchkiss, Jason T; Lesher, Ruth
2018-06-01
This study predicted Burnout from the self-care practices, compassion satisfaction, secondary traumatic stress, and organizational factors among chaplains who participated from all 50 states (N = 534). A hierarchical regression model indicated that the combined effect of compassion satisfaction, secondary traumatic stress, mindful self-care, demographic, and organizational factors explained 83.2% of the variance in Burnout. Chaplains serving in a hospital were slightly more at risk for Burnout than those in hospice or other settings. Organizational factors that most predicted Burnout were feeling bogged down by the "system" (25.7%) and an overwhelming caseload (19.9%). Each self-care category was a statistically significant protective factor against Burnout risk. The strongest protective factors against Burnout in order of strength were self-compassion and purpose, supportive structure, mindful self-awareness, mindful relaxation, supportive relationships, and physical care. For secondary traumatic stress, supportive structure, mindful self-awareness, and self-compassion and purpose were the strongest protective factors. Chaplains who engaged in multiple and frequent self-care strategies experienced higher professional quality of life and low Burnout risk. In the chaplain's journey toward wellness, a reflective practice of feeling good about doing good and mindful self-care are vital. The significance, implications, and limitations of the study were discussed.
Smoking among American adolescents: a risk and protective factor analysis.
Scal, Peter; Ireland, Marjorie; Borowsky, Iris Wagman
2003-04-01
Cigarette smoking remains a substantial threat to the current and future health of America's youth. The purpose of this study was to identify the risk and protective factors for cigarette smoking among US adolescents. Data from the National Longitudinal Study of Adolescent Health was used, comparing the responses of all non-smokers at Time 1 for their ability to predict the likelihood of smoking at Time 2, one year later. Data was stratified into four gender by grade group cohorts. Cross-cutting risk factors for smoking among all four cohorts were: using alcohol, marijuana, and other illicit drugs; violence involvement; having had sex; having friends who smoke and learning problems. Having a higher grade point average and family connectedness were protective across all cohorts. Other gender and grade group specific risk and protective factors were identified. The estimated probability of initiating smoking decreased by 19.2% to 54.1% both in situations of high and low risk as the number of protective factors present increased. Of the factors that predict or protect against smoking some are influential across all gender and grade group cohorts studied, while others are specific to gender and developmental stage. Prevention efforts that target both the reduction of risk factors and enhancement of protective factors at the individual, family, peer group and community are likely to reduce the likelihood of smoking initiation.
Ferguson, Christopher J
2011-06-01
Research on youth mental health has increasingly indicated the importance of multivariate analyses of multiple risk factors for negative outcomes. Television and video game use have often been posited as potential contributors to attention problems, but previous studies have not always been well-controlled or used well-validated outcome measures. The current study examines the multivariate nature of risk factors for attention problems symptomatic of attention deficit hyperactivity disorder and poor school performance. A predominantly Hispanic population of 603 children (ages 10-14) and their parents/guardians responded to multiple behavioral measures. Outcome measures included parent and child reported attention problem behaviors on the Child Behavior Checklist (CBCL) as well as poor school performance as measured by grade point average (GPA). Results found that internal factors such as male gender, antisocial traits, family environment and anxiety best predicted attention problems. School performance was best predicted by family income. Television and video game use, whether total time spent using, or exposure to violent content specifically, did not predict attention problems or GPA. Television and video game use do not appear to be significant predictors of childhood attention problems. Intervention and prevention efforts may be better spent on other risk factors. Copyright © 2010 Elsevier Ltd. All rights reserved.
Rabinovich, Anat; Cohen, Jacqueline M; Kahn, Susan R
2014-06-01
The post thrombotic syndrome (PTS) develops in 20-40% of deep venous thrombosis (DVT) patients. Risk factors for PTS have not been well elucidated. Identification of risk factors would facilitate individualised risk assessment for PTS. We conducted a systematic review to determine whether biomarkers of fibrinolysis or endothelial dysfunction can predict the risk for PTS among DVT patients. Studies were identified by searching the electronic databases PubMed, EMBASE, Scopus and Web of science. We included studies published between 1990 and 2013, measured biomarker levels in adult DVT patients, and reported rates of PTS development. Fourteen studies were included: 11 investigated the association between D-dimer and PTS; three examined fibrinogen; two measured von Willebrand factor; one measured plasminogen activator inhibitor-1; one assessed ADAMTS-13 (A Disintegrin and Metalloprotease with Thrombospondin type 1 repeats) and one measured factor XIII activity. Studies varied with regards to inclusion criteria, definition of PTS, time point and method of biomarker measurement. We were unable to meta-analyse results due to marked clinical heterogeneity. Descriptively, a significant association with PTS was found for D-dimer in four studies and factor XIII in one study. Further prospective research is needed to elucidate whether these markers might be useful to predict PTS development.
Razmara, Jafar; Zaboli, Mohammad Hassan; Hassankhani, Hadi
2016-11-01
Falls play a critical role in older people's life as it is an important source of morbidity and mortality in elders. In this article, elders fall risk is predicted based on a physiological profile approach using a multilayer neural network with back-propagation learning algorithm. The personal physiological profile of 200 elders was collected through a questionnaire and used as the experimental data for learning and testing the neural network. The profile contains a series of simple factors putting elders at risk for falls such as vision abilities, muscle forces, and some other daily activities and grouped into two sets: psychological factors and public factors. The experimental data were investigated to select factors with high impact using principal component analysis. The experimental results show an accuracy of ≈90 percent and ≈87.5 percent for fall prediction among the psychological and public factors, respectively. Furthermore, combining these two datasets yield an accuracy of ≈91 percent that is better than the accuracy of single datasets. The proposed method suggests a set of valid and reliable measurements that can be employed in a range of health care systems and physical therapy to distinguish people who are at risk for falls.
Petoumenos, Kathy; Worm, Signe W; Fontas, Eric; Weber, Rainer; De Wit, Stephane; Bruyand, Mathias; Reiss, Peter; El-Sadr, Wafaa; Monforte, Antonella D'Arminio; Friis-Møller, Nina; Lundgren, Jens D; Law, Matthew G
2012-01-01
Introduction HIV-positive patients receiving combination antiretroviral therapy (cART) frequently experience metabolic complications such as dyslipidemia and insulin resistance, as well as lipodystrophy, increasing the risk of cardiovascular disease (CVD) and diabetes mellitus (DM). Rates of DM and other glucose-associated disorders among HIV-positive patients have been reported to range between 2 and 14%, and in an ageing HIV-positive population, the prevalence of DM is expected to continue to increase. This study aims to develop a model to predict the short-term (six-month) risk of DM in HIV-positive populations and to compare the existing models developed in the general population. Methods All patients recruited to the Data Collection on Adverse events of Anti-HIV Drugs (D:A:D) study with follow-up data, without prior DM, myocardial infarction or other CVD events and with a complete DM risk factor profile were included. Conventional risk factors identified in the general population as well as key HIV-related factors were assessed using Poisson-regression methods. Expected probabilities of DM events were also determined based on the Framingham Offspring Study DM equation. The D:A:D and Framingham equations were then assessed using an internal-external validation process; area under the receiver operating characteristic (AUROC) curve and predicted DM events were determined. Results Of 33,308 patients, 16,632 (50%) patients were included, with 376 cases of new onset DM during 89,469 person-years (PY). Factors predictive of DM included higher glucose, body mass index (BMI) and triglyceride levels, and older age. Among HIV-related factors, recent CD4 counts of<200 cells/µL and lipodystrophy were predictive of new onset DM. The mean performance of the D:A:D and Framingham equations yielded AUROC of 0.894 (95% CI: 0.849, 0.940) and 0.877 (95% CI: 0.823, 0.932), respectively. The Framingham equation over-predicted DM events compared to D:A:D for lower glucose and lower triglycerides, and for BMI levels below 25 kg/m2. Conclusions The D:A:D equation performed well in predicting the short-term onset of DM in the validation dataset and for specific subgroups provided better estimates of DM risk than the Framingham. PMID:23078769
Risk factors of hepatitis B virus infection among blood donors in Duhok city, Kurdistan Region, Iraq
R Hussein, Nawfal
2018-01-01
Background: Hepatitis B virus (HBV) infection is a public health problem. The lack of information about the seroprevalence and risk factors is an obstacle for preventive public health plans to reduce the burden of viral hepatitis. Therefore, this study was conducted in Iraq, where no studies had been performed to determine the prevalence and risk factors of HBV infection. Methods: Blood samples were collected form 438 blood donors attending blood bank in Duhok city. Serum samples were tested for HBV core-antibodies (HBcAb) and HBV surface-antigen (HBsAg) by ELISA. Various risk factors were recorded and multivariate analysis was performed. Results: 5/438 (1.14%) of the subjects were HBsAg positive (HBsAg and HBcAb positive) and 36/438 (8.2%) were HBcAb positive. Hence, 41 cases were exposed to HBV and data analysis was based on that. Univariate analysis showed that there were significant associations between history of illegitimate sexual contact, history of alcohol or history of dental surgeries and HBV exposure (p<0.05 for all). Then, multivariate analysis was conducted to find HBV exposure predictive factors. It was found that history of dental surgery was a predictive factor for exposure to the virus (P=0.03, OR: 2.397). Conclusions: This study suggested that the history of dental surgery was predictive for HBV transmission in Duhok city. Further population-based study is needed to determine HBV risk factors in the society and public health plan based on that should be considered. PMID:29387315
Bravo, Adrian J; Anthenien, Amber M; Prince, Mark A; Pearson, Matthew R
2017-06-01
Given that both marijuana use and cannabis use disorder peak among college students, it is imperative to determine the factors that may reduce risk of problematic marijuana use and/or the development of cannabis use disorder. From a harm reduction perspective, the present study examined whether the use of marijuana protective behavioral strategies (PBS) buffers or amplifies the effects of several distinct risk and protective factors that have been shown to relate to marijuana-related outcomes (i.e., use frequency and consequences). Specifically, we examined marijuana-PBS use as a moderator of the effects of impulsivity-like traits, marijuana use motives, gender, and marijuana use frequency on marijuana-related outcomes in a large sample of college students (n=2093 past month marijuana users across 11 universities). In all models PBS use was robustly related with use frequency and consequences (i.e., strongly negatively associated with marijuana outcomes). Among interactions, we found: 1) unique significant interactions between specific impulsivity-like traits (i.e., premeditation, perseverance, and sensation seeking) and marijuana-PBS use in predicting marijuana consequences, 2) unique significant interactions between each marijuana use motive and marijuana-PBS use in predicting marijuana use frequency and 3) marijuana-PBS use buffered the risk associated with male gender in predicting both marijuana outcomes. Our results suggest that marijuana-PBS use can buffer risk factors and enhance protective factors among marijuana using college students. Future research is needed to understand context-specific factors and individual-level factors that may make marijuana-PBS use more effective. Copyright © 2017 Elsevier Ltd. All rights reserved.
Christensen, Daniel; Zubrick, Stephen R; Lawrence, David; Mitrou, Francis; Taylor, Catherine L
2014-01-01
Receptive vocabulary development is a component of the human language system that emerges in the first year of life and is characterised by onward expansion throughout life. Beginning in infancy, children's receptive vocabulary knowledge builds the foundation for oral language and reading skills. The foundations for success at school are built early, hence the public health policy focus on reducing developmental inequalities before children start formal school. The underlying assumption is that children's development is stable, and therefore predictable, over time. This study investigated this assumption in relation to children's receptive vocabulary ability. We investigated the extent to which low receptive vocabulary ability at 4 years was associated with low receptive vocabulary ability at 8 years, and the predictive utility of a multivariate model that included child, maternal and family risk factors measured at 4 years. The study sample comprised 3,847 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Multivariate logistic regression was used to investigate risks for low receptive vocabulary ability from 4-8 years and sensitivity-specificity analysis was used to examine the predictive utility of the multivariate model. In the multivariate model, substantial risk factors for receptive vocabulary delay from 4-8 years, in order of descending magnitude, were low receptive vocabulary ability at 4 years, low maternal education, and low school readiness. Moderate risk factors, in order of descending magnitude, were low maternal parenting consistency, socio-economic area disadvantage, low temperamental persistence, and NESB status. The following risk factors were not significant: One or more siblings, low family income, not reading to the child, high maternal work hours, and Aboriginal or Torres Strait Islander ethnicity. The results of the sensitivity-specificity analysis showed that a well-fitted multivariate model featuring risks of substantive magnitude does not do particularly well in predicting low receptive vocabulary ability from 4-8 years.
Gilman, Stephen E.; Dupuy, Jamie M.; Perlis, Roy H.
2013-01-01
Objective It is currently not possible to determine which individuals with unipolar depression are at highest risk for a manic episode. This study investigates clinical and psychosocial risk factors for mania among individuals with major depressive disorder (MDD), indicating diagnostic conversion from MDD to bipolar I disorder. Methods We fitted logistic regression models to predict the first onset of a manic episode among 6,214 cases of lifetime MDD according to DSM-IV criteria in the National Epidemiologic Survey on Alcohol and Related Conditions. Results Approximately 1 in 20 individuals with MDD transitioned to bipolar disorder during the study's 3-year follow-up period. Demographic risk factors for the transition from MDD to bipolar disorder included younger age, Black race/ethnicity, and less than high school education. Clinical characteristics of depression (e.g., age at first onset, presence of atypical features) were not associated with diagnostic conversion. However, prior psychopathology was associated with the transition to bipolar disorder: history of social phobia (Odds Ratio=2.20; 95% Confidence Interval=1.47, 3.30) and generalized anxiety disorder (OR=1.58; CI=1.06, 2.35). Lastly, we identified environmental stressors over the life course that predicted the transition to bipolar disorder: these include a history of child abuse (OR=1.26; CI=1.12, 1.42) and past-year problems with one's social support group (OR=1.79; CI=1.19, 2.68). The overall predictive power of these risk factors based on a receiver operating curve analysis is modest. Conclusions A wide range of demographic, clinical, and environmental risk factors were identified that indicate a heightened risk for the transition to bipolar disorder. Additional work is needed to further enhance the prediction of bipolar disorder among cases of MDD, and to determine whether interventions targeting these factors could reduce the risk of bipolar disorder. PMID:22394428
ERIC Educational Resources Information Center
Bennett, David S.; Bendersky, Margaret; Lewis, Michael
2002-01-01
Examined 4-year-olds for effects on IQ of prenatal cocaine exposure, exposure to other substances, risk factors, and neonatal medical problems. Found that maternal verbal IQ and low environmental risk predicted child IQ. Cocaine exposure negatively predicted children's overall IQ and verbal reasoning scores for boys only. Maternal harsh…
Graham, Alice M; Kim, Hyoun K; Fisher, Philip A
2012-02-01
Aggression between partners represents a potential guiding force in family dynamics. However, research examining the influence of partner aggression (physically and psychologically aggressive acts by both partners) on harsh parenting and young child adjustment has been limited by a frequent focus on low-risk samples and by the examination of partner aggression at a single time point. Especially in the context of multiple risk factors and around transitions such as childbirth, partner aggression might be better understood as a dynamic process. In the present study, longitudinal trajectories of partner aggression from birth to age 3 years in a large, high-risk, and ethnically diverse sample (N = 461) were examined. Specific risk factors were tested as predictors of aggression over time, and the longitudinal effects of partner aggression on maternal harsh parenting and child maladjustment were examined. Partner aggression decreased over time, with higher maternal depression and lower maternal age predicting greater decreases in partner aggression. While taking into account contextual and psychosocial risk factors, higher partner aggression measured at birth and a smaller decrease over time independently predicted higher levels of maternal harsh parenting at age 3 years. Initial level of partner aggression and change over time predicted child maladjustment indirectly (via maternal harsh parenting). The implications of understanding change in partner aggression over time as a path to harsh parenting and young children's maladjustment in the context of multiple risk factors are discussed.
Graham, Alice M.; Kim, Hyoun K.; Fisher, Philip A.
2012-01-01
Aggression between partners represents a potential guiding force in family dynamics. However, research examining the influence of partner aggression (physically and psychologically aggressive acts by both partners) on harsh parenting and young child adjustment has been limited by a frequent focus on low risk samples and by the examination of partner aggression at a single time point. Especially in the context of multiple risk factors and around transitions such as childbirth, partner aggression might be better understood as a dynamic process. In the present study, longitudinal trajectories of partner aggression from birth to age 3 years in a large, high-risk, and ethnically diverse sample (N = 461) were examined. Specific risk factors were tested as predictors of aggression over time, and the longitudinal effects of partner aggression on maternal harsh parenting and child maladjustment were examined. Partner aggression decreased over time, with higher maternal depression and lower maternal age predicting greater decreases in partner aggression. While taking into account contextual and psychosocial risk factors, higher partner aggression measured at birth and a smaller decrease over time independently predicted higher levels of maternal harsh parenting at age 3 years. Initial level of partner aggression and change over time predicted child maladjustment indirectly (via maternal harsh parenting). The implications of understanding change in partner aggression over time as a path to harsh parenting and young children's maladjustment in the context of multiple risk factors are discussed. PMID:22201248
Bourdaud, Nathalie; Devys, Jean-Michel; Bientz, Jocelyne; Lejus, Corinne; Hebrard, Anne; Tirel, Olivier; Lecoutre, Damien; Sabourdin, Nada; Nivoche, Yves; Baujard, Catherine; Nikasinovic, Lydia; Orliaguet, Gilles A
2014-09-01
Few data are available in the literature on risk factors for postoperative vomiting (POV) in children. The aim of the study was to establish independent risk factors for POV and to construct a pediatric specific risk score to predict POV in children. Characteristics of 2392 children operated under general anesthesia were recorded. The dataset was randomly split into an evaluation set (n = 1761), analyzed with a multivariate analysis including logistic regression and backward stepwise procedure, and a validation set (n = 450), used to confirm the accuracy of prediction using the area under the receiver operating characteristic curve (ROCAUC ), to optimize sensitivity and specificity. The overall incidence of POV was 24.1%. Five independent risk factors were identified: stratified age (>3 and <6 or >13 years: adjusted OR 2.46 [95% CI 1.75-3.45]; ≥6 and ≤13 years: aOR 3.09 [95% CI 2.23-4.29]), duration of anesthesia (aOR 1.44 [95% IC 1.06-1.96]), surgery at risk (aOR 2.13 [95% IC 1.49-3.06]), predisposition to POV (aOR 1.81 [95% CI 1.43-2.31]), and multiple opioids doses (aOR 2.76 [95% CI 2.06-3.70], P < 0.001). A simplified score was created, ranging from 0 to 6 points. Respective incidences of POV were 5%, 6%, 13%, 21%, 36%, 48%, and 52% when the risk score ranged from 0 to 6. The model yielded a ROCAUC of 0.73 [95% CI 0.67-0.78] when applied to the validation dataset. Independent risk factors for POV were identified and used to create a new score to predict which children are at high risk of POV. © 2014 John Wiley & Sons Ltd.
Risk score for predicting long-term mortality after coronary artery bypass graft surgery.
Wu, Chuntao; Camacho, Fabian T; Wechsler, Andrew S; Lahey, Stephen; Culliford, Alfred T; Jordan, Desmond; Gold, Jeffrey P; Higgins, Robert S D; Smith, Craig R; Hannan, Edward L
2012-05-22
No simplified bedside risk scores have been created to predict long-term mortality after coronary artery bypass graft surgery. The New York State Cardiac Surgery Reporting System was used to identify 8597 patients who underwent isolated coronary artery bypass graft surgery in July through December 2000. The National Death Index was used to ascertain patients' vital statuses through December 31, 2007. A Cox proportional hazards model was fit to predict death after CABG surgery using preprocedural risk factors. Then, points were assigned to significant predictors of death on the basis of the values of their regression coefficients. For each possible point total, the predicted risks of death at years 1, 3, 5, and 7 were calculated. It was found that the 7-year mortality rate was 24.2 in the study population. Significant predictors of death included age, body mass index, ejection fraction, unstable hemodynamic state or shock, left main coronary artery disease, cerebrovascular disease, peripheral arterial disease, congestive heart failure, malignant ventricular arrhythmia, chronic obstructive pulmonary disease, diabetes mellitus, renal failure, and history of open heart surgery. The points assigned to these risk factors ranged from 1 to 7; possible point totals for each patient ranged from 0 to 28. The observed and predicted risks of death at years 1, 3, 5, and 7 across patient groups stratified by point totals were highly correlated. The simplified risk score accurately predicted the risk of mortality after coronary artery bypass graft surgery and can be used for informed consent and as an aid in determining treatment choice.
Lifetime risks for aneurysmal subarachnoid haemorrhage: multivariable risk stratification.
Vlak, Monique H M; Rinkel, Gabriel J E; Greebe, Paut; Greving, Jacoba P; Algra, Ale
2013-06-01
The overall incidence of aneurysmal subarachnoid haemorrhage (aSAH) in western populations is around 9 per 100 000 person-years, which confers to a lifetime risk of around half per cent. Risk factors for aSAH are usually expressed as relative risks and suggest that absolute risks vary considerably according to risk factor profiles, but such estimates are lacking. We aimed to estimate incidence and lifetime risks of aSAH according to risk factor profiles. We used data from 250 patients admitted with aSAH and 574 sex-matched and age-matched controls, who were randomly retrieved from general practitioners files. We determined independent prognostic factors with multivariable logistic regression analyses and assessed discriminatory performance using the area under the receiver operating characteristic curve. Based on the prognostic model we predicted incidences and lifetime risks of aSAH for different risk factor profiles. The four strongest independent predictors for aSAH, namely current smoking (OR 6.0; 95% CI 4.1 to 8.6), a positive family history for aSAH (4.0; 95% CI 2.3 to 7.0), hypertension (2.4; 95% CI 1.5 to 3.8) and hypercholesterolaemia (0.2; 95% CI 0.1 to 0.4), were used in the final prediction model. This model had an area under the receiver operating characteristic curve of 0.73 (95% CI 0.69 to 0.76). Depending on sex, age and the four predictors, the incidence of aSAH ranged from 0.4/100 000 to 298/100 000 person-years and lifetime risk between 0.02% and 7.2%. The incidence and lifetime risk of aSAH in the general population varies widely according to risk factor profiles. Whether persons with high risks benefit from screening should be assessed in cost-effectiveness studies.
Lipid-related markers and cardiovascular disease prediction.
Di Angelantonio, Emanuele; Gao, Pei; Pennells, Lisa; Kaptoge, Stephen; Caslake, Muriel; Thompson, Alexander; Butterworth, Adam S; Sarwar, Nadeem; Wormser, David; Saleheen, Danish; Ballantyne, Christie M; Psaty, Bruce M; Sundström, Johan; Ridker, Paul M; Nagel, Dorothea; Gillum, Richard F; Ford, Ian; Ducimetiere, Pierre; Kiechl, Stefan; Koenig, Wolfgang; Dullaart, Robin P F; Assmann, Gerd; D'Agostino, Ralph B; Dagenais, Gilles R; Cooper, Jackie A; Kromhout, Daan; Onat, Altan; Tipping, Robert W; Gómez-de-la-Cámara, Agustín; Rosengren, Annika; Sutherland, Susan E; Gallacher, John; Fowkes, F Gerry R; Casiglia, Edoardo; Hofman, Albert; Salomaa, Veikko; Barrett-Connor, Elizabeth; Clarke, Robert; Brunner, Eric; Jukema, J Wouter; Simons, Leon A; Sandhu, Manjinder; Wareham, Nicholas J; Khaw, Kay-Tee; Kauhanen, Jussi; Salonen, Jukka T; Howard, William J; Nordestgaard, Børge G; Wood, Angela M; Thompson, Simon G; Boekholdt, S Matthijs; Sattar, Naveed; Packard, Chris; Gudnason, Vilmundur; Danesh, John
2012-06-20
The value of assessing various emerging lipid-related markers for prediction of first cardiovascular events is debated. To determine whether adding information on apolipoprotein B and apolipoprotein A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 to total cholesterol and high-density lipoprotein cholesterol (HDL-C) improves cardiovascular disease (CVD) risk prediction. Individual records were available for 165,544 participants without baseline CVD in 37 prospective cohorts (calendar years of recruitment: 1968-2007) with up to 15,126 incident fatal or nonfatal CVD outcomes (10,132 CHD and 4994 stroke outcomes) during a median follow-up of 10.4 years (interquartile range, 7.6-14 years). Discrimination of CVD outcomes and reclassification of participants across predicted 10-year risk categories of low (<10%), intermediate (10%-<20%), and high (≥20%) risk. The addition of information on various lipid-related markers to total cholesterol, HDL-C, and other conventional risk factors yielded improvement in the model's discrimination: C-index change, 0.0006 (95% CI, 0.0002-0.0009) for the combination of apolipoprotein B and A-I; 0.0016 (95% CI, 0.0009-0.0023) for lipoprotein(a); and 0.0018 (95% CI, 0.0010-0.0026) for lipoprotein-associated phospholipase A2 mass. Net reclassification improvements were less than 1% with the addition of each of these markers to risk scores containing conventional risk factors. We estimated that for 100,000 adults aged 40 years or older, 15,436 would be initially classified at intermediate risk using conventional risk factors alone. Additional testing with a combination of apolipoprotein B and A-I would reclassify 1.1%; lipoprotein(a), 4.1%; and lipoprotein-associated phospholipase A2 mass, 2.7% of people to a 20% or higher predicted CVD risk category and, therefore, in need of statin treatment under Adult Treatment Panel III guidelines. In a study of individuals without known CVD, the addition of information on the combination of apolipoprotein B and A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 mass to risk scores containing total cholesterol and HDL-C led to slight improvement in CVD prediction.
Testing a cognitive model to predict posttraumatic stress disorder following childbirth.
King, Lydia; McKenzie-McHarg, Kirstie; Horsch, Antje
2017-01-14
One third of women describes their childbirth as traumatic and between 0.8 and 6.9% goes on to develop posttraumatic stress disorder (PTSD). The cognitive model of PTSD has been shown to be applicable to a range of trauma samples. However, childbirth is qualitatively different to other trauma types and special consideration needs to be taken when applying it to this population. Previous studies have investigated some cognitive variables in isolation but no study has so far looked at all the key processes described in the cognitive model. This study therefore aimed to investigate whether theoretically-derived variables of the cognitive model explain unique variance in postnatal PTSD symptoms when key demographic, obstetric and clinical risk factors are controlled for. One-hundred and fifty-seven women who were between 1 and 12 months post-partum (M = 6.5 months) completed validated questionnaires assessing PTSD and depressive symptoms, childbirth experience, postnatal social support, trauma memory, peritraumatic processing, negative appraisals, dysfunctional cognitive and behavioural strategies and obstetric as well as demographic risk factors in an online survey. A PTSD screening questionnaire suggested that 5.7% of the sample might fulfil diagnostic criteria for PTSD. Overall, risk factors alone predicted 43% of variance in PTSD symptoms and cognitive behavioural factors alone predicted 72.7%. A final model including both risk factors and cognitive behavioural factors explained 73.7% of the variance in PTSD symptoms, 37.1% of which was unique variance predicted by cognitive factors. All variables derived from Ehlers and Clark's cognitive model significantly explained variance in PTSD symptoms following childbirth, even when clinical, demographic and obstetric were controlled for. Our findings suggest that the CBT model is applicable and useful as a way of understanding and informing the treatment of PTSD following childbirth.
Ferguson, Christopher J; Cricket Meehan, D
2010-12-01
The current study examines risk and protective factors for youth antisocial personality and behavior from a multivariate format. It is hoped that this research will elucidate those risk and protective factors most important for focus of future prevention and intervention efforts. The current study examines multiple factors associated with youth antisocial traits and behavior in a sample of 8,256 youth (mean age 14), with the goal of identifying the strongest and most consistent risk or protective factors. Data was collected from the Ohio version of the Youth Risk Behavior Surveillance System's (YRBSS) school-based Youth Risk Behavior Survey (YRBS) developed by the Centers for Disease Control (CDC). Hierarchical multiple regression analyses identified peer delinquency, drug use and negative community influences as predictive of antisocial traits. Schools and families functioned as protective factors. Youth who fought frequently tended to be male, antisocial, dug using, depressed, and associated with delinquent peers. Weapons carrying was most common among drug using, antisocial males. Television and video game use were not predictive of antisocial, fighting or weapons carrying outcomes. Developmental patterns across age ranges regarding the relative importance of specific risk factors were also examined. Strategies for intervention and prevention of youth violence that focus on peers, neighborhoods, depression, and families may be particularly likely to bear fruit.
Evaluating the vulnerability of Maine forests to wind damage
Thomas E. Perry; Jeremy S. Wilson
2010-01-01
Numerous factors, some of which cannot be controlled, are continually interacting with the forest resource, introducing risk to management, and making consistent predictable management outcomes uncertain. Included in these factors are threats or hazards such as windstorms and wildfire. Factors influencing the probability (risk) of windthrow or windsnap occurring can be...
Body Dissatisfaction of Adolescent Girls and Boys: Risk and Resource Factors.
ERIC Educational Resources Information Center
Barker, Erin T.; Galambos, Nancy L.
2003-01-01
Examined factors predicting body dissatisfaction for seventh- and tenth-grade girls and boys in the second wave of a 3-year study of psychosocial maturity. Identified high body mass index, greater figure management, and being teased about appearance as risk factors for girls' body dissatisfaction. Being teased was boys' only significant risk…
Peigh, Graham; Cavarocchi, Nicholas; Keith, Scott W; Hirose, Hitoshi
2015-10-01
Although the use of cardiac extracorporeal membrane oxygenation (ECMO) is increasing in adult patients, the field lacks understanding of associated risk factors. While standard intensive care unit risk scores such as SAPS II (simplified acute physiology score II), SOFA (sequential organ failure assessment), and APACHE II (acute physiology and chronic health evaluation II), or disease-specific scores such as MELD (model for end-stage liver disease) and RIFLE (kidney risk, injury, failure, loss of function, ESRD) exist, they may not apply to adult cardiac ECMO patients as their risk factors differ from variables used in these scores. Between 2010 and 2014, 73 ECMOs were performed for cardiac support at our institution. Patient demographics and survival were retrospectively analyzed. A new easily calculated score for predicting ECMO mortality was created using identified risk factors from univariate and multivariate analyses, and model discrimination was compared with other scoring systems. Cardiac ECMO was performed on 73 patients (47 males and 26 females) with a mean age of 48 ± 14 y. Sixty-four percent of patients (47/73) survived ECMO support. Pre-ECMO SAPS II, SOFA, APACHE II, MELD, RIFLE, PRESERVE, and ECMOnet scores, were not correlated with survival. Univariate analysis of pre-ECMO risk factors demonstrated that increased lactate, renal dysfunction, and postcardiotomy cardiogenic shock were risk factors for death. Applying these data into a new simplified cardiac ECMO score (minimal risk = 0, maximal = 5) predicted patient survival. Survivors had a lower risk score (1.8 ± 1.2) versus the nonsurvivors (3.0 ± 0.99), P < 0.0001. Common intensive care unit or disease-specific risk scores calculated for cardiac ECMO patients did not correlate with ECMO survival, whereas a new simplified cardiac ECMO score provides survival predictability. Copyright © 2015 Elsevier Inc. All rights reserved.
Job stress models for predicting burnout syndrome: a review.
Chirico, Francesco
2016-01-01
In Europe, the Council Directive 89/391 for improvement of workers' safety and health has emphasized the importance of addressing all occupational risk factors, and hence also psychosocial and organizational risk factors. Nevertheless, the construct of "work-related stress" elaborated from EU-OSHA is not totally corresponding with the "psychosocial" risk, that is a broader category of risk, comprising various and different psychosocial risk factors. The term "burnout", without any binding definition, tries to integrate symptoms as well as cause of the burnout process. In Europe, the most important methods developed for the work related stress risk assessment are based on the Cox's transactional model of job stress. Nevertheless, there are more specific models for predicting burnout syndrome. This literature review provides an overview of job burnout, highlighting the most important models of job burnout, such as the Job Strain, the Effort/Reward Imbalance and the Job Demands-Resources models. The difference between these models and the Cox's model of job stress is explored.
Retinopathy of prematurity: a review of risk factors and their clinical significance.
Kim, Sang Jin; Port, Alexander D; Swan, Ryan; Campbell, J Peter; Chan, R V Paul; Chiang, Michael F
2018-04-19
Retinopathy of prematurity (ROP) is a retinal vasoproliferative disease that affects premature infants. Despite improvements in neonatal care and management guidelines, ROP remains a leading cause of childhood blindness worldwide. Current screening guidelines are primarily based on two risk factors: birth weight and gestational age; however, many investigators have suggested other risk factors, including maternal factors, prenatal and perinatal factors, demographics, medical interventions, comorbidities of prematurity, nutrition, and genetic factors. We review the existing literature addressing various possible ROP risk factors. Although there have been contradictory reports, and the risk may vary between different populations, understanding ROP risk factors is essential to develop predictive models, to gain insights into pathophysiology of retinal vascular diseases and diseases of prematurity, and to determine future directions in management of and research in ROP. Copyright © 2018 Elsevier Inc. All rights reserved.
Bao, Yixia; Chen, Zhimin; Liu, Enmei; Xiang, Li; Zhao, Deyu; Hong, Jianguo
2017-11-18
The aim of this study was to identify risk factors of asthma among children < 6 years old (preschool age) for predicting asthma during the preschool age and early school age (≤ 10 years of age). MEDLINE, Cochrane, EMBASE, and Google Scholar databases were searched until June 30, 2017. Prospective or retrospective cohort and case-control studies were included. Studies had to have evaluated risk factors or a predictive model for developing asthma in children ≤ 6 years of age or persistent asthma in early school age. A total of 17 studies were included in the analysis. Factors associated with developing asthma in children ≤ 10 years of age (both pre-school and early school age) included male gender (pooled OR = 1.70, P < 0.001), atopic dermatitis (pooled OR = 2.02, P < 0.001), a family history of asthma (pooled OR = 2.20, P < 0.001), and serum IgE levels ≥ 60 kU/l or having specific IgE (pooled OR = 2.36, P < 0.001). A history of exposure to smoke or wheezing was also associated with persistent asthma in early school age (pooled OR = 1.51, P = 0.030 and pooled OR = 2.59, P < 0.001, respectively). In general, asthma predictive models (e.g., API, PIAMA, PAPS) had relatively low sensitivity (range, 21% to 71.4%) but high specificity (range, 69% to 98%). The study found that male gender, exposure to smoke, atopic dermatitis, family history of asthma, history of wheezing, and serum IgE level ≥ 60 kU/l or having specific IgE were significantly associated with developing asthma by either preschool or early school age. Asthma predictive models can be developed by those risk factors.
Improving prediction of fall risk among nursing home residents using electronic medical records.
Marier, Allison; Olsho, Lauren E W; Rhodes, William; Spector, William D
2016-03-01
Falls are physically and financially costly, but may be preventable with targeted intervention. The Minimum Data Set (MDS) is one potential source of information on fall risk factors among nursing home residents, but its limited breadth and relatively infrequent updates may limit its practical utility. Richer, more frequently updated data from electronic medical records (EMRs) may improve ability to identify individuals at highest risk for falls. The authors applied a repeated events survival model to analyze MDS 3.0 and EMR data for 5129 residents in 13 nursing homes within a single large California chain that uses a centralized EMR system from a leading vendor. Estimated regression parameters were used to project resident fall probability. The authors examined the proportion of observed falls within each projected fall risk decile to assess improvements in predictive power from including EMR data. In a model incorporating fall risk factors from the MDS only, 28.6% of observed falls occurred among residents in the highest projected risk decile. In an alternative specification incorporating more frequently updated measures for the same risk factors from the EMR data, 32.3% of observed falls occurred among residents in the highest projected risk decile, a 13% increase over the base MDS-only specification. Incorporating EMR data improves ability to identify those at highest risk for falls relative to prediction using MDS data alone. These improvements stem chiefly from the greater frequency with which EMR data are updated, with minimal additional gains from availability of additional risk factor variables. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Kaplan, Robert C; McGinn, Aileen P; Baird, Alison E; Hendrix, Susan L; Kooperberg, Charles; Lynch, John; Rosenbaum, Daniel M; Johnson, Karen C; Strickler, Howard D; Wassertheil-Smoller, Sylvia
2009-01-01
Background Inflammatory and hemostasis-related biomarkers may identify women at risk of stroke. Methods Hormones and Biomarkers Predicting Stroke is a study of ischemic stroke among postmenopausal women participating in the Women’s Health Initiative Observational Study (n = 972 case-control pairs). A Biomarker Risk Score was derived from levels of seven inflammatory and hemostasis-related biomarkers that appeared individually to predict risk of ischemic stroke: C-reactive protein, interleukin-6, tissue plasminogen activator, D-dimer, white blood cell count, neopterin, and homocysteine. The c index was used to evaluate discrimination. Results Of all the individual biomarkers examined, C-reactive protein emerged as the only independent single predictor of ischemic stroke (adjusted odds ratio comparing Q4 versus Q1 = 1.64, 95% confidence interval: 1.15–2.32, p = 0.01) after adjustment for other biomarkers and standard stroke risk factors. The Biomarker Risk Score identified a gradient of increasing stroke risk with a greater number of elevated inflammatory/hemostasis biomarkers, and improved the c index significantly compared with standard stroke risk factors (p = 0.02). Among the subset of individuals who met current criteria for “high risk” levels of C-reactive protein (> 3.0 mg/L), the Biomarker Risk Score defined an approximately two-fold gradient of risk. We found no evidence for a relationship between stroke and levels of E-selectin, fibrinogen, tumor necrosis factor-alpha, vascular cell adhesion molecule-1, prothrombin fragment 1+2, Factor VIIC, or plasminogen activator inhibitor-1 antigen (p >0.15). Discussion The findings support the further exploration of multiple-biomarker panels to develop approaches for stratifying an individual’s risk of stroke. PMID:18984425
Acute Brain Dysfunction: Development and Validation of a Daily Prediction Model.
Marra, Annachiara; Pandharipande, Pratik P; Shotwell, Matthew S; Chandrasekhar, Rameela; Girard, Timothy D; Shintani, Ayumi K; Peelen, Linda M; Moons, Karl G M; Dittus, Robert S; Ely, E Wesley; Vasilevskis, Eduard E
2018-03-24
The goal of this study was to develop and validate a dynamic risk model to predict daily changes in acute brain dysfunction (ie, delirium and coma), discharge, and mortality in ICU patients. Using data from a multicenter prospective ICU cohort, a daily acute brain dysfunction-prediction model (ABD-pm) was developed by using multinomial logistic regression that estimated 15 transition probabilities (from one of three brain function states [normal, delirious, or comatose] to one of five possible outcomes [normal, delirious, comatose, ICU discharge, or died]) using baseline and daily risk factors. Model discrimination was assessed by using predictive characteristics such as negative predictive value (NPV). Calibration was assessed by plotting empirical vs model-estimated probabilities. Internal validation was performed by using a bootstrap procedure. Data were analyzed from 810 patients (6,711 daily transitions). The ABD-pm included individual risk factors: mental status, age, preexisting cognitive impairment, baseline and daily severity of illness, and daily administration of sedatives. The model yielded very high NPVs for "next day" delirium (NPV: 0.823), coma (NPV: 0.892), normal cognitive state (NPV: 0.875), ICU discharge (NPV: 0.905), and mortality (NPV: 0.981). The model demonstrated outstanding calibration when predicting the total number of patients expected to be in any given state across predicted risk. We developed and internally validated a dynamic risk model that predicts the daily risk for one of three cognitive states, ICU discharge, or mortality. The ABD-pm may be useful for predicting the proportion of patients for each outcome state across entire ICU populations to guide quality, safety, and care delivery activities. Copyright © 2018 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.
Jackson, Rod
2017-01-01
Background Many national cardiovascular disease (CVD) risk factor management guidelines now recommend that drug treatment decisions should be informed primarily by patients’ multi-variable predicted risk of CVD, rather than on the basis of single risk factor thresholds. To investigate the potential impact of treatment guidelines based on CVD risk thresholds at a national level requires individual level data representing the multi-variable CVD risk factor profiles for a country’s total adult population. As these data are seldom, if ever, available, we aimed to create a synthetic population, representing the joint CVD risk factor distributions of the adult New Zealand population. Methods and results A synthetic population of 2,451,278 individuals, representing the actual age, gender, ethnicity and social deprivation composition of people aged 30–84 years who completed the 2013 New Zealand census was generated using Monte Carlo sampling. Each ‘synthetic’ person was then probabilistically assigned values of the remaining cardiovascular disease (CVD) risk factors required for predicting their CVD risk, based on data from the national census national hospitalisation and drug dispensing databases and a large regional cohort study, using Monte Carlo sampling and multiple imputation. Where possible, the synthetic population CVD risk distributions for each non-demographic risk factor were validated against independent New Zealand data sources. Conclusions We were able to develop a synthetic national population with realistic multi-variable CVD risk characteristics. The construction of this population is the first step in the development of a micro-simulation model intended to investigate the likely impact of a range of national CVD risk management strategies that will inform CVD risk management guideline updates in New Zealand and elsewhere. PMID:28384217
Knight, Josh; Wells, Susan; Marshall, Roger; Exeter, Daniel; Jackson, Rod
2017-01-01
Many national cardiovascular disease (CVD) risk factor management guidelines now recommend that drug treatment decisions should be informed primarily by patients' multi-variable predicted risk of CVD, rather than on the basis of single risk factor thresholds. To investigate the potential impact of treatment guidelines based on CVD risk thresholds at a national level requires individual level data representing the multi-variable CVD risk factor profiles for a country's total adult population. As these data are seldom, if ever, available, we aimed to create a synthetic population, representing the joint CVD risk factor distributions of the adult New Zealand population. A synthetic population of 2,451,278 individuals, representing the actual age, gender, ethnicity and social deprivation composition of people aged 30-84 years who completed the 2013 New Zealand census was generated using Monte Carlo sampling. Each 'synthetic' person was then probabilistically assigned values of the remaining cardiovascular disease (CVD) risk factors required for predicting their CVD risk, based on data from the national census national hospitalisation and drug dispensing databases and a large regional cohort study, using Monte Carlo sampling and multiple imputation. Where possible, the synthetic population CVD risk distributions for each non-demographic risk factor were validated against independent New Zealand data sources. We were able to develop a synthetic national population with realistic multi-variable CVD risk characteristics. The construction of this population is the first step in the development of a micro-simulation model intended to investigate the likely impact of a range of national CVD risk management strategies that will inform CVD risk management guideline updates in New Zealand and elsewhere.
Unravelling the structure of species extinction risk for predictive conservation science.
Lee, Tien Ming; Jetz, Walter
2011-05-07
Extinction risk varies across species and space owing to the combined and interactive effects of ecology/life history and geography. For predictive conservation science to be effective, large datasets and integrative models that quantify the relative importance of potential factors and separate rapidly changing from relatively static threat drivers are urgently required. Here, we integrate and map in space the relative and joint effects of key correlates of The International Union for Conservation of Nature-assessed extinction risk for 8700 living birds. Extinction risk varies significantly with species' broad-scale environmental niche, geographical range size, and life-history and ecological traits such as body size, developmental mode, primary diet and foraging height. Even at this broad scale, simple quantifications of past human encroachment across species' ranges emerge as key in predicting extinction risk, supporting the use of land-cover change projections for estimating future threat in an integrative setting. A final joint model explains much of the interspecific variation in extinction risk and provides a remarkably strong prediction of its observed global geography. Our approach unravels the species-level structure underlying geographical gradients in extinction risk and offers a means of disentangling static from changing components of current and future threat. This reconciliation of intrinsic and extrinsic, and of past and future extinction risk factors may offer a critical step towards a more continuous, forward-looking assessment of species' threat status based on geographically explicit environmental change projections, potentially advancing global predictive conservation science.
Yokoyama, Yukihiro; Ebata, Tomoki; Igami, Tsuyoshi; Sugawara, Gen; Mizuno, Takashi; Yamaguchi, Junpei; Nagino, Masato
2016-06-01
Postoperative liver failure (PHLF) is one of the most common complications following major hepatectomy. The preoperative assessment of future liver remnant (FLR) function is critical to predict the incidence of PHLF. To determine the efficacy of the plasma clearance rate of indocyanine green clearance of FLR (ICGK-F) in predicting PHLF in cases of highly invasive hepatectomy with extrahepatic bile duct resection. Five hundred and eighty-five patients who underwent major hepatectomy with extrahepatic bile duct resection, from 2002 to 2014 in a single institution, were evaluated. Among them, 192 patients (33 %) had PHLF. The predictive value of ICGK-F for PHLF was determined and compared with other risk factors for PHLF. The incidence of PHLF was inversely proportional to the level of ICGK-F. With multivariate logistic regression analysis, ICGK-F, combined pancreatoduodenectomy, the operation time, and blood loss were identified as independent risk factors of PHLF. The risk of PHLF increased according to the decrement of ICGK-F (the odds ratio of ICGK-F for each decrement of 0.01 was 1.22; 95 % confidence interval 1.12-1.33; P < 0.001). Low ICGK-F was also identified as an independent risk factor predicting the postoperative mortality. ICGK-F is useful in predicting the PHLF and mortality in patients undergoing major hepatectomy with extrahepatic bile duct resection. This criterion may be useful for highly invasive hepatectomy, such as that with extrahepatic bile duct resection.
Very early predictors of conduct problems and crime: results from a national cohort study.
Murray, Joseph; Irving, Barrie; Farrington, David P; Colman, Ian; Bloxsom, Claire A J
2010-11-01
Longitudinal research has produced a wealth of knowledge about individual, family, and social predictors of crime. However, nearly all studies have started after children are age 5, and little is known about earlier risk factors. The 1970 British Cohort Study is a prospective population survey of more than 16,000 children born in 1970. Pregnancy, birth, child, parent, and socioeconomic characteristics were measured from medical records, parent interviews, and child assessments at birth and age 5. Conduct problems were reported by parents at age 10, and criminal convictions were self-reported by study members at ages 30-34. Early (up to age 5) psychosocial risk factors were strong predictors of conduct problems and criminal conviction. Among pregnancy and birth measures, only prenatal maternal smoking was strongly predictive. Risk factors were similar for girls and boys. Additive risk scores predicted antisocial behaviour quite strongly. Risk factors from pregnancy to age 5 are quite strong predictors of conduct problems and crime. New risk assessment tools could be developed to identify young children at high risk for later antisocial behaviour. © 2010 The Authors. Journal of Child Psychology and Psychiatry © 2010 Association for Child and Adolescent Mental Health.
[Psychosocial risk factors at work as predictors of mobbing].
Meseguer de Pedro, Mariano; Soler Sánchez, María I; García-Izquierdo, Mariano; Sáez Navarro, M C; Sánchez Meca, Julio
2007-05-01
This work analyses the way in which various psychosocial risk indicators may predict mobbing. A sample of 638 workers, 168 men and 470 women, from the fruit-and-vegetable sector was evaluated. An anonymous questionnaire was administered to all employees who were present on the evaluation days in the companies comprising the study. After analysing the data obtained with the mobbing questionnaire NAQ-RE (Sáez, García-Izquierdo, and Llor, 2003) and with the psychosocial risk factors evaluation method of the INSHT (Martín and Pérez, 1997), using canonical regression, we found that several psychosocial factors such as role definition, mental workload, interest in the workers, and supervision / participation predict two types of mobbing: personal mobbing and work-performance-related mobbing.
Aagaard, Theis; Roen, Ashley; Daugaard, Gedske; Brown, Peter; Sengeløv, Henrik; Mocroft, Amanda; Lundgren, Jens; Helleberg, Marie
2017-01-01
Abstract Background Febrile neutropenia (FN) is a common complication to chemotherapy associated with a high burden of morbidity and mortality. Reliable prediction of individual risk based on pretreatment risk factors allows for stratification of preventive interventions. We aimed to develop such a risk stratification model to predict FN in the 30 days after initiation of chemotherapy. Methods We included consecutive treatment-naïve patients with solid cancers and diffuse large B-cell lymphomas at Copenhagen University Hospital, 2010–2015. Data were obtained from the PERSIMUNE repository of electronic health records. FN was defined as neutrophils ≤0.5 × 10E9/L at the time of either a blood culture sample or death. Time from initiation of chemotherapy to FN was analyzed using Fine-Gray models with death as a competing event. Risk factors investigated were: age, sex, body surface area, haemoglobin, albumin, neutrophil-to-lymphocyte ratio, Charlson Comorbidity Index (CCI) and chemotherapy drugs. Parameter estimates were scaled and summed to create the risk score. The scores were grouped into four: low, intermediate, high and very high risk. Results Among 8,585 patients, 467 experienced FN, incidence rate/30 person-days 0.05 (95% CI, 0.05–0.06). Age (1 point if > 65 years), albumin (1 point if < 39 g/L), CCI (1 point if > 2) and chemotherapy (range -5 to 6 points/drug) predicted FN. Median score at inclusion was 2 points (range –5 to 9). The cumulative incidence and the incidence rates and hazard ratios of FN are shown in Figure 1 and Table 1, respectively. Conclusion We developed a risk score to predict FN the first month after initiation of chemotherapy. The score is easy to use and provides good differentiation of risk groups; the score needs independent validation before routine use. Disclosures All authors: No reported disclosures.
Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes.
Nowak, Christoph; Carlsson, Axel C; Östgren, Carl Johan; Nyström, Fredrik H; Alam, Moudud; Feldreich, Tobias; Sundström, Johan; Carrero, Juan-Jesus; Leppert, Jerzy; Hedberg, Pär; Henriksen, Egil; Cordeiro, Antonio C; Giedraitis, Vilmantas; Lind, Lars; Ingelsson, Erik; Fall, Tove; Ärnlöv, Johan
2018-05-24
Multiplex proteomics could improve understanding and risk prediction of major adverse cardiovascular events (MACE) in type 2 diabetes. This study assessed 80 cardiovascular and inflammatory proteins for biomarker discovery and prediction of MACE in type 2 diabetes. We combined data from six prospective epidemiological studies of 30-77-year-old individuals with type 2 diabetes in whom 80 circulating proteins were measured by proximity extension assay. Multivariable-adjusted Cox regression was used in a discovery/replication design to identify biomarkers for incident MACE. We used gradient-boosted machine learning and lasso regularised Cox regression in a random 75% training subsample to assess whether adding proteins to risk factors included in the Swedish National Diabetes Register risk model would improve the prediction of MACE in the separate 25% test subsample. Of 1211 adults with type 2 diabetes (32% women), 211 experienced a MACE over a mean (±SD) of 6.4 ± 2.3 years. We replicated associations (<5% false discovery rate) between risk of MACE and eight proteins: matrix metalloproteinase (MMP)-12, IL-27 subunit α (IL-27a), kidney injury molecule (KIM)-1, fibroblast growth factor (FGF)-23, protein S100-A12, TNF receptor (TNFR)-1, TNFR-2 and TNF-related apoptosis-inducing ligand receptor (TRAIL-R)2. Addition of the 80-protein assay to established risk factors improved discrimination in the separate test sample from 0.686 (95% CI 0.682, 0.689) to 0.748 (95% CI 0.746, 0.751). A sparse model of 20 added proteins achieved a C statistic of 0.747 (95% CI 0.653, 0.842) in the test sample. We identified eight protein biomarkers, four of which are novel, for risk of MACE in community residents with type 2 diabetes, and found improved risk prediction by combining multiplex proteomics with an established risk model. Multiprotein arrays could be useful in identifying individuals with type 2 diabetes who are at highest risk of a cardiovascular event.
Liau, Siow Yen; Mohamed Izham, M I; Hassali, M A; Shafie, A A
2010-01-01
Cardiovascular diseases, the main causes of hospitalisations and death globally, have put an enormous economic burden on the healthcare system. Several risk factors are associated with the occurrence of cardiovascular events. At the heart of efficient prevention of cardiovascular disease is the concept of risk assessment. This paper aims to review the available cardiovascular risk-assessment tools and its applicability in predicting cardiovascular risk among Asian populations. A systematic search was performed using keywords as MeSH and Boolean terms. A total of 25 risk-assessment tools were identified. Of these, only two risk-assessment tools (8%) were derived from an Asian population. These risk-assessment tools differ in various ways, including characteristics of the derivation sample, type of study, time frame of follow-up, end points, statistical analysis and risk factors included. Very few cardiovascular risk-assessment tools were developed in Asian populations. In order to accurately predict the cardiovascular risk of our population, there is a need to develop a risk-assessment tool based on local epidemiological data.
Shen, Jiabin; Li, Shaohua; Xiang, Huiyun; Pang, Shulan; Xu, Guozhang; Schwebel, David C.
2013-01-01
This study examines demographic, cognitive and behavioral factors that predict pediatric dog-bite injury risk in rural China. A total of 1,537 children (grades 4–6) in rural regions of Anhui, Hebei and Zhejiang Provinces, China completed self-report questionnaires assessing beliefs about and behaviors with dogs. The results showed that almost 30% of children reported a history of dog bites. Children answered 56% of dog-safety knowledge items correctly. Regressions revealed both demographic and cognitive/behavioral factors predicted children’s risky interactions with dogs and dog-bite history. Boys behaved more riskily with dogs and were more frequently bitten. Older children reported greater risks with dogs and more bites. With demographics controlled, attitudes/beliefs of invulnerability, exposure frequency, and dog ownership predicted children’s self-reported risky practice with dogs. Attitudes/beliefs of invulnerability, dog exposure, and dog ownership predicted dog bites. In conclusion, both demographic and cognitive/behavioral factors influenced rural Chinese children’s dog-bite injury risk. Theory-based, empirically-supported intervention programs might reduce dog-bite injuries in rural China. PMID:23470881
Aiyer, Sophie M.; Wilson, Melvin N.; Shaw, Daniel S.; Dishion, Thomas J.
2013-01-01
The ecology of the emergence of psycho-pathology in early childhood is often approached by the analysis of a limited number of contextual risk factors. In the present study, we provide a comprehensive analysis of ecological risk by conducting a canonical correlation analysis of 13 risk factors at child age 2 and seven narrow-band scales of internalizing and externalizing problem behaviors at child age 4, using a sample of 364 geographically and ethnically diverse, disadvantaged primary caregivers, alternative caregivers, and preschool-age children. Participants were recruited from Special Supplemental Nutrition Program for Women, Infants, and Children sites and were screened for family risk. Canonical correlation analysis revealed that (1) a first latent combination of family and individual risks of caregivers predicted combinations of child emotional and behavioral problems, and that (2) a second latent combination of contextual and structural risks predicted child somatic complaints. Specifically, (1) the combination of chaotic home, conflict with child, parental depression, and parenting hassles predicted a co-occurrence of internalizing and externalizing behaviors, and (2) the combination of father absence, perceived discrimination, neighborhood danger, and fewer children living in the home predicted child somatic complaints. The research findings are discussed in terms of the development of psychopathology, as well as the potential prevention needs of families in high-risk contexts. PMID:23700232
Abell, Sally K.; De Courten, Barbora; Boyle, Jacqueline A.; Teede, Helena J.
2015-01-01
Understanding pathophysiology and identifying mothers at risk of major pregnancy complications is vital to effective prevention and optimal management. However, in current antenatal care, understanding of pathophysiology of complications is limited. In gestational diabetes mellitus (GDM), risk prediction is mostly based on maternal history and clinical risk factors and may not optimally identify high risk pregnancies. Hence, universal screening is widely recommended. Here, we will explore the literature on GDM and biomarkers including inflammatory markers, adipokines, endothelial function and lipids to advance understanding of pathophysiology and explore risk prediction, with a goal to guide prevention and treatment of GDM. PMID:26110385
McElroy, Erika M; Rodriguez, Christina M
2008-08-01
Utilizing the conceptual framework of the Social Information Processing (SIP) model (Milner, 1993, 2000), associations between cognitive risk factors and child physical abuse risk and maladaptive discipline style and practices were examined in an at-risk population. Seventy-three mothers of 5-12-year-old children, who were identified by their therapist as having an externalizing behavior problem, responded to self-report measures pertaining to cognitive risk factors (empathic perspective taking, frustration tolerance, developmental expectations, parenting locus of control), abuse risk, and discipline style and practices. The Child Behavior Checklist (CBCL) provided a confirmation of the child's externalizing behaviors independent of the therapist's assessment. The results of this study suggest several cognitive risk factors significantly predict risk of parental aggression toward children. A parent's ability to empathize and take the perspective of their child, parental locus of control, and parental level of frustration tolerance were significant predictors of abuse potential (accounting for 63% of the variance) and inappropriate discipline practices (accounting for 55% of the variance). Findings of the present study provide support for processes theorized in the SIP model. Specifically, results underscore the potential role of parents' frustration tolerance, developmental expectations, locus of control, and empathy as predictive of abuse potential and disciplinary style in an at-risk sample.
Aliberti, Stefano; Di Pasquale, Marta; Zanaboni, Anna Maria; Cosentini, Roberto; Brambilla, Anna Maria; Seghezzi, Sonia; Tarsia, Paolo; Mantero, Marco; Blasi, Francesco
2012-02-15
Not all risk factors for acquiring multidrug-resistant (MDR) organisms are equivalent in predicting pneumonia caused by resistant pathogens in the community. We evaluated risk factors for acquiring MDR bacteria in patients coming from the community who were hospitalized with pneumonia. Our evaluation was based on actual infection with a resistant pathogen and clinical outcome during hospitalization. An observational, prospective study was conducted on consecutive patients coming from the community who were hospitalized with pneumonia. Data on admission and during hospitalization were collected. Logistic regression models were used to evaluate risk factors for acquiring MDR bacteria independently associated with the actual presence of a resistant pathogen and in-hospital mortality. Among the 935 patients enrolled in the study, 473 (51%) had at least 1 risk factor for acquiring MDR bacteria on admission. Of all risk factors, hospitalization in the preceding 90 days (odds ratio [OR], 4.87 95% confidence interval {CI}, 1.90-12.4]; P = .001) and residency in a nursing home (OR, 3.55 [95% CI, 1.12-11.24]; P = .031) were independent predictors for an actual infection with a resistant pathogen. A score able to predict pneumonia caused by a resistant pathogen was computed, including comorbidities and risk factors for MDR. Hospitalization in the preceding 90 days and residency in a nursing home were also independent predictors for in-hospital mortality. Risk factors for acquiring MDR bacteria should be weighted differently, and a probabilistic approach to identifying resistant pathogens among patients coming from the community with pneumonia should be embraced.
Feinstein, Matthew J.; Nance, Robin M.; Drozd, Daniel R.; Ning, Hongyan; Delaney, Joseph A.; Heckbert, Susan R.; Budoff, Matthew J.; Mathews, William C.; Kitahata, Mari M.; Saag, Michael S.; Eron, Joseph J.; Moore, Richard D.; Achenbach, Chad J.; Lloyd-Jones, Donald M.; Crane, Heidi M.
2017-01-01
Importance Persons with human immunodeficiency virus (HIV) treated with antiretroviral therapy (ART) have improved longevity but are at elevated risk for myocardial infarction (MI) due to common MI risk factors and HIV-specific factors. Despite these elevated MI rates, optimal methods to predict MI risks for HIV-infected persons remain unclear. Objective To determine the extent to which existing and de novo estimation tools predict MI in a multi-center HIV cohort with rigorous MI adjudication. Design We evaluated the performance of standard-of-care and two new data-derived MI risk estimation models in the Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) multi-center prospective clinical cohort. The new risk estimation models were validated in a cohort separate from the derivation cohort. Setting Clinical sites across the U.S. where HIV-infected adults receive medical care in inpatient and outpatient settings. Participants HIV-infected adults receiving care anytime since 1995 at 5 CNICS sites where MIs were adjudicated (N=19829). Exposures Common cardiovascular risk factors, HIV viral load, CD4 count, and medication use were used to calculate predicted event rates. Main Outcome and Measures Observed MI rates over the course of follow-up, scaled to 10 years using an observed prime approach to account for dropout and loss to follow-up prior to 10 years. Results MI rates were higher among blacks, older participants, and participants who were not virally suppressed. The 2013 Pooled Cohort Equations (PCEs), which predict composite rates of MI and stroke, adequately discriminated MI risk (Harrell’s C Statistic = 0.75). Two data-derived models incorporating HIV-specific covariates exhibited weak calibration in a validation sample and did not discriminate risk any better (Harrell’s C Statistic = 0.72 and 0.73) than the PCEs. The PCEs were moderately calibrated in CNICS but predicted consistently lower than observed prime rates of MI. The PCEs Conclusions and relevance The PCEs discriminated MI risk and were moderately calibrated in this multi-center HIV cohort. Adding HIV-specific factors did not improve model performance. As HIV-infected cohorts capture and assess outcomes of MI and stroke, the performance of risk estimation tools should be revisited. PMID:28002550
Kabaria, Caroline W; Molteni, Fabrizio; Mandike, Renata; Chacky, Frank; Noor, Abdisalan M; Snow, Robert W; Linard, Catherine
2016-07-30
With more than half of Africa's population expected to live in urban settlements by 2030, the burden of malaria among urban populations in Africa continues to rise with an increasing number of people at risk of infection. However, malaria intervention across Africa remains focused on rural, highly endemic communities with far fewer strategic policy directions for the control of malaria in rapidly growing African urban settlements. The complex and heterogeneous nature of urban malaria requires a better understanding of the spatial and temporal patterns of urban malaria risk in order to design effective urban malaria control programs. In this study, we use remotely sensed variables and other environmental covariates to examine the predictability of intra-urban variations of malaria infection risk across the rapidly growing city of Dar es Salaam, Tanzania between 2006 and 2014. High resolution SPOT satellite imagery was used to identify urban environmental factors associated malaria prevalence in Dar es Salaam. Supervised classification with a random forest classifier was used to develop high resolution land cover classes that were combined with malaria parasite prevalence data to identify environmental factors that influence localized heterogeneity of malaria transmission and develop a high resolution predictive malaria risk map of Dar es Salaam. Results indicate that the risk of malaria infection varied across the city. The risk of infection increased away from the city centre with lower parasite prevalence predicted in administrative units in the city centre compared to administrative units in the peri-urban suburbs. The variation in malaria risk within Dar es Salaam was shown to be influenced by varying environmental factors. Higher malaria risks were associated with proximity to dense vegetation, inland water and wet/swampy areas while lower risk of infection was predicted in densely built-up areas. The predictive maps produced can serve as valuable resources for municipal councils aiming to shrink the extents of malaria across cities, target resources for vector control or intensify mosquito and disease surveillance. The semi-automated modelling process developed can be replicated in other urban areas to identify factors that influence heterogeneity in malaria risk patterns and detect vulnerable zones. There is a definite need to expand research into the unique epidemiology of malaria transmission in urban areas for focal elimination and sustained control agendas.
Wu, Ming-Kung; Lu, Yan-Ting; Huang, Chi-Wei; Lin, Pin-Hsuan; Chen, Nai-Ching; Lui, Chun-Chung; Chang, Wen-Neng; Lee, Chen-Chang; Chang, Ya-Ting; Chen, Sz-Fan; Chang, Chiung-Chih
2015-07-01
Cerebrovascular risk factors and white matter (WM) damage lead to worse cognitive performance in Alzheimer dementia (AD). This study investigated WM microstructure using diffusion tensor imaging in patients with mild to moderate AD and investigated specific fiber tract involvement with respect to predefined cerebrovascular risk factors and neurobehavioral data prediction cross-sectionally and after 18 months. To identify the primary pathoanatomic relationships of risk biomarkers to fiber tract integrity, we predefined 11 major association tracts and calculated tract specific fractional anisotropy (FA) values. Eighty-five patients with AD underwent neurobehavioral assessments including the minimental state examination (MMSE) and 12-item neuropsychiatric inventory twice with a 1.5-year interval to represent major outcome factors. In the cross-sectional data, total cholesterol, low-density lipoprotein, vitamin B12, and homocysteine levels correlated variably with WM FA values. After entering the biomarkers and WM FA into a regression model to predict neurobehavioral outcomes, only fiber tract FA or homocysteine level predicted the MMSE score, and fiber tract FA or age predicted the neuropsychiatric inventory total scores and subdomains of apathy, disinhibition, and aberrant motor behavior. In the follow-up neurobehavioral data, the mean global FA value predicted the MMSE and aberrant motor behavior subdomain, while age predicted the anxiety and elation subdomains. Cerebrovascular risk biomarkers may modify WM microstructural organization, while the association with fiber integrity showed greater clinical significance to the prediction of neurobehavioral outcomes both cross-sectionally and longitudinally.
Parent-child communication processes: preventing children's health-risk behavior.
Riesch, Susan K; Anderson, Lori S; Krueger, Heather A
2006-01-01
Review individual, family, and environmental factors that predict health-risk behavior among children and to propose parent-child communication processes as a mechanism to mediate them. Improving parent-child communication processes may: reduce individual risk factors, such as poor academic achievement or self-esteem; modify parenting practices such as providing regulation and structure and acting as models of health behavior; and facilitate discussion about factors that lead to involvement in health-risk behaviors. Assessment strategies to identify youth at risk for health-risk behavior are recommended and community-based strategies to improve communication among parents and children need development.
Psychological Language on Twitter Predicts County-Level Heart Disease Mortality
Eichstaedt, Johannes C.; Schwartz, Hansen Andrew; Kern, Margaret L.; Park, Gregory; Labarthe, Darwin R.; Merchant, Raina M.; Jha, Sneha; Agrawal, Megha; Dziurzynski, Lukasz A.; Sap, Maarten; Weeg, Christopher; Larson, Emily E.; Ungar, Lyle H.; Seligman, Martin E. P.
2015-01-01
Hostility and chronic stress are known risk factors for heart disease, but they are costly to assess on a large scale. We used language expressed on Twitter to characterize community-level psychological correlates of age-adjusted mortality from atherosclerotic heart disease (AHD). Language patterns reflecting negative social relationships, disengagement, and negative emotions—especially anger—emerged as risk factors; positive emotions and psychological engagement emerged as protective factors. Most correlations remained significant after controlling for income and education. A cross-sectional regression model based only on Twitter language predicted AHD mortality significantly better than did a model that combined 10 common demographic, socioeconomic, and health risk factors, including smoking, diabetes, hypertension, and obesity. Capturing community psychological characteristics through social media is feasible, and these characteristics are strong markers of cardiovascular mortality at the community level. PMID:25605707
Psychological language on Twitter predicts county-level heart disease mortality.
Eichstaedt, Johannes C; Schwartz, Hansen Andrew; Kern, Margaret L; Park, Gregory; Labarthe, Darwin R; Merchant, Raina M; Jha, Sneha; Agrawal, Megha; Dziurzynski, Lukasz A; Sap, Maarten; Weeg, Christopher; Larson, Emily E; Ungar, Lyle H; Seligman, Martin E P
2015-02-01
Hostility and chronic stress are known risk factors for heart disease, but they are costly to assess on a large scale. We used language expressed on Twitter to characterize community-level psychological correlates of age-adjusted mortality from atherosclerotic heart disease (AHD). Language patterns reflecting negative social relationships, disengagement, and negative emotions-especially anger-emerged as risk factors; positive emotions and psychological engagement emerged as protective factors. Most correlations remained significant after controlling for income and education. A cross-sectional regression model based only on Twitter language predicted AHD mortality significantly better than did a model that combined 10 common demographic, socioeconomic, and health risk factors, including smoking, diabetes, hypertension, and obesity. Capturing community psychological characteristics through social media is feasible, and these characteristics are strong markers of cardiovascular mortality at the community level. © The Author(s) 2014.
Studying Biology to Understand Risk: Dosimetry Models and Quantitative Adverse Outcome Pathways
Confidence in the quantitative prediction of risk is increased when the prediction is based to as great an extent as possible on the relevant biological factors that constitute the pathway from exposure to adverse outcome. With the first examples now over 40 years old, physiologi...
ERIC Educational Resources Information Center
Layne, Christopher M.; Olsen, Joseph A.; Baker, Aaron; Legerski, John-Paul; Isakson, Brian; Pasalic, Alma; Durakovic-Belko, Elvira; Dapo, Nermin; Campara, Nihada; Arslanagic, Berina; Saltzman, William R.; Pynoos, Robert S.
2010-01-01
Methods are needed for quantifying the potency and differential effects of risk factors to identify at-risk groups for theory building and intervention. Traditional methods for constructing war exposure measures are poorly suited to "unpack" differential relations between specific types of exposure and specific outcomes. This study of…
ERIC Educational Resources Information Center
Greene, Jamie G.; And Others
1983-01-01
Addresses three questions: (1) To what extent do risk factors of prematurity and illness affect neonatal characteristics? (2) Do these risk factors continue to account for differences in mother and infant social interactive behavior at three months? and (three) To what degree are neonatal characteristics predictive of mother and infant behavior at…
Bernecker, Samantha L; Rosellini, Anthony J; Nock, Matthew K; Chiu, Wai Tat; Gutierrez, Peter M; Hwang, Irving; Joiner, Thomas E; Naifeh, James A; Sampson, Nancy A; Zaslavsky, Alan M; Stein, Murray B; Ursano, Robert J; Kessler, Ronald C
2018-04-03
High rates of mental disorders, suicidality, and interpersonal violence early in the military career have raised interest in implementing preventive interventions with high-risk new enlistees. The Army Study to Assess Risk and Resilience in Servicemembers (STARRS) developed risk-targeting systems for these outcomes based on machine learning methods using administrative data predictors. However, administrative data omit many risk factors, raising the question whether risk targeting could be improved by adding self-report survey data to prediction models. If so, the Army may gain from routinely administering surveys that assess additional risk factors. The STARRS New Soldier Survey was administered to 21,790 Regular Army soldiers who agreed to have survey data linked to administrative records. As reported previously, machine learning models using administrative data as predictors found that small proportions of high-risk soldiers accounted for high proportions of negative outcomes. Other machine learning models using self-report survey data as predictors were developed previously for three of these outcomes: major physical violence and sexual violence perpetration among men and sexual violence victimization among women. Here we examined the extent to which this survey information increases prediction accuracy, over models based solely on administrative data, for those three outcomes. We used discrete-time survival analysis to estimate a series of models predicting first occurrence, assessing how model fit improved and concentration of risk increased when adding the predicted risk score based on survey data to the predicted risk score based on administrative data. The addition of survey data improved prediction significantly for all outcomes. In the most extreme case, the percentage of reported sexual violence victimization among the 5% of female soldiers with highest predicted risk increased from 17.5% using only administrative predictors to 29.4% adding survey predictors, a 67.9% proportional increase in prediction accuracy. Other proportional increases in concentration of risk ranged from 4.8% to 49.5% (median = 26.0%). Data from an ongoing New Soldier Survey could substantially improve accuracy of risk models compared to models based exclusively on administrative predictors. Depending upon the characteristics of interventions used, the increase in targeting accuracy from survey data might offset survey administration costs.
A risk score for predicting near-term incidence of hypertension: the Framingham Heart Study.
Parikh, Nisha I; Pencina, Michael J; Wang, Thomas J; Benjamin, Emelia J; Lanier, Katherine J; Levy, Daniel; D'Agostino, Ralph B; Kannel, William B; Vasan, Ramachandran S
2008-01-15
Studies suggest that targeting high-risk, nonhypertensive individuals for treatment may delay hypertension onset, thereby possibly mitigating vascular complications. Risk stratification may facilitate cost-effective approaches to management. To develop a simple risk score for predicting hypertension incidence by using measures readily obtained in the physician's office. Longitudinal cohort study. Framingham Heart Study, Framingham, Massachusetts. 1717 nonhypertensive white individuals 20 to 69 years of age (mean age, 42 years; 54% women), without diabetes and with both parents in the original cohort of the Framingham Heart Study, contributed 5814 person-examinations. Scores were developed for predicting the 1-, 2-, and 4-year risk for new-onset hypertension, and performance characteristics of the prediction algorithm were assessed by using calibration and discrimination measures. Parental hypertension was ascertained from examinations of the original cohort of the Framingham Heart Study. During follow-up (median time over all person-examinations, 3.8 years), 796 persons (52% women) developed new-onset hypertension. In multivariable analyses, age, sex, systolic and diastolic blood pressure, body mass index, parental hypertension, and cigarette smoking were significant predictors of hypertension. According to the risk score based on these factors, the 4-year risk for incident hypertension was classified as low (<5%) in 34% of participants, medium (5% to 10%) in 19%, and high (>10%) in 47%. The c-statistic for the prediction model was 0.788, and calibration was very good. The risk score findings may not be generalizable to persons of nonwhite race or ethnicity or to persons with diabetes. The risk score algorithm has not been validated in an independent cohort and is based on single measurements of risk factors and blood pressure. The hypertension risk prediction score can be used to estimate an individual's absolute risk for hypertension on short-term follow-up, and it represents a simple, office-based tool that may facilitate management of high-risk individuals with prehypertension.
Prospective Prediction of Functional Difficulties among Recently Separated Veterans
2014-01-01
while factors following separation from the military have a primary role in predicting functional difficulties during reintegration into civilian...and protective factors for functional difficulties among Veterans. In a sample of recently separated Marines, we used stepwise logistic and multiple...military, posttraumatic stress disorder, prospective, PTSD, reintegration, risk factors , Veterans, work functioning . INTRODUCTION Studies suggest that Iraq
Using chronic disease risk factors to adjust Medicare capitation payments
Schauffler, Helen Halpin; Howland, Jonathan; Cobb, Janet
1992-01-01
This study evaluates the use of risk factors for chronic disease as health status adjusters for Medicare's capitation formula, the average adjusted per capita costs (AAPCC). Risk factor data for the surviving members of the Framingham Study cohort who were examined in 1982-83 were merged with 100 percent Medicare payment data for 1984 and 1985, matching on Social Security number and sex. Seven different AAPCC models were estimated to assess the independent contributions of risk factors and measures of prior utilization and disability in increasing the explanatory power of AAPCC. The findings suggest that inclusion of risk factors for chronic disease as health status adjusters can improve substantially the predictive accuracy of AAPCC. PMID:10124441
[Early prediction of the neurological result at 12 months in newborns at neurological risk].
Herbón, F; Garibotti, G; Moguilevsky, J
2015-08-01
The aim of this study was to evaluate the Amiel-Tison neurological examination (AT) and cranial ultrasound at term for predicting the neurological result at 12 months in newborns with neurological risk. The study included 89 newborns with high risk of neurological damage, who were discharged from the Neonatal Intensive Care of the Hospital Zonal Bariloche, Argentina. The assessment consisted of a neurological examination and cranial ultrasound at term, and neurological examination and evaluation of development at 12 months. The sensitivity, specificity, positive and negative predictor value was calculated. The relationship between perinatal factors and neurodevelopment at 12 month of age was also calculated using logistic regression models. Seventy children completed the follow-up. At 12 months of age, 14% had an abnormal neurological examination, and 17% abnormal development. The neurological examination and the cranial ultrasound at term had low sensitivity to predict abnormal neurodevelopment. At 12 months, 93% of newborns with normal AT showed normal neurological results, and 86% normal development. Among newborns with normal cranial ultrasound the percentages were 90 and 81%, respectively. Among children with three or more perinatal risk factors, the frequency of abnormalities in the neurological response was 5.4 times higher than among those with fewer risk factors, and abnormal development was 3.5 times more frequent. The neurological examination and cranial ultrasound at term had low sensitivity but high negative predictive value for the neurodevelopment at 12 months. Three or more perinatal risk factors were associated with neurodevelopment abnormalities at 12 months of age. Copyright © 2014 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.
Sutton, Rosemary; Venn, Nicola C; Law, Tamara; Boer, Judith M; Trahair, Toby N; Ng, Anthea; Den Boer, Monique L; Dissanayake, Anuruddhika; Giles, Jodie E; Dalzell, Pauline; Mayoh, Chelsea; Barbaric, Draga; Revesz, Tamas; Alvaro, Frank; Pieters, Rob; Haber, Michelle; Norris, Murray D; Schrappe, Martin; Dalla Pozza, Luciano; Marshall, Glenn M
2018-02-01
To prevent relapse, high risk paediatric acute lymphoblastic leukaemia (ALL) is treated very intensively. However, most patients who eventually relapse have standard or medium risk ALL with low minimal residual disease (MRD) levels. We analysed recurrent microdeletions and other clinical prognostic factors in a cohort of 475 uniformly treated non-high risk precursor B-cell ALL patients with the aim of better predicting relapse and refining risk stratification. Lower relapse-free survival at 7 years (RFS) was associated with IKZF1 intragenic deletions (P < 0·0001); P2RY8-CRLF2 gene fusion (P < 0·0004); Day 33 MRD>5 × 10 -5 (P < 0·0001) and High National Cancer Institute (NCI) risk (P < 0·0001). We created a predictive model based on a risk score (RS) for deletions, MRD and NCI risk, extending from an RS of 0 (RS0) for patients with no unfavourable factors to RS2 + for patients with 2 or 3 high risk factors. RS0, RS1, and RS2 + groups had RFS of 93%, 78% and 49%, respectively, and overall survival (OS) of 99%, 91% and 71%. The RS provided greater discrimination than MRD-based risk stratification into standard (89% RFS, 96% OS) and medium risk groups (79% RFS, 91% OS). We conclude that this RS may enable better early therapeutic stratification and thus improve cure rates for childhood ALL. © 2017 John Wiley & Sons Ltd.
Wang, Hai-Qing; Yang, Jian; Yang, Jia-Yin; Wang, Wen-Tao; Yan, Lu-Nan
2015-08-01
Liver resection is a major surgery requiring perioperative blood transfusion. Predicting the need for blood transfusion for patients undergoing liver resection is of great importance. The present study aimed to develop and validate a model for predicting transfusion requirement in HBV-related hepatocellular carcinoma patients undergoing liver resection. A total of 1543 consecutive liver resections were included in the study. Randomly selected sample set of 1080 cases (70% of the study cohort) were used to develop a predictive score for transfusion requirement and the remaining 30% (n=463) was used to validate the score. Based on the preoperative and predictable intraoperative parameters, logistic regression was used to identify risk factors and to create an integer score for the prediction of transfusion requirement. Extrahepatic procedure, major liver resection, hemoglobin level and platelets count were identified as independent predictors for transfusion requirement by logistic regression analysis. A score system integrating these 4 factors was stratified into three groups which could predict the risk of transfusion, with a rate of 11.4%, 24.7% and 57.4% for low, moderate and high risk, respectively. The prediction model appeared accurate with good discriminatory abilities, generating an area under the receiver operating characteristic curve of 0.736 in the development set and 0.709 in the validation set. We have developed and validated an integer-based risk score to predict perioperative transfusion for patients undergoing liver resection in a high-volume surgical center. This score allows identifying patients at a high risk and may alter transfusion practices.
Yamashita, Shimpei; Kohjimoto, Yasuo; Iguchi, Takashi; Koike, Hiroyuki; Kusumoto, Hiroki; Iba, Akinori; Kikkawa, Kazuro; Kodama, Yoshiki; Matsumura, Nagahide; Hara, Isao
2016-03-22
While novel drugs have been developed, docetaxel remains one of the standard initial systemic therapies for castration-resistant prostate cancer (CRPC) patients. Despite the excellent anti-tumor effect of docetaxel, its severe adverse effects sometimes distress patients. Therefore, it would be very helpful to predict the efficacy of docetaxel before treatment. The aims of this study were to evaluate the potential value of patient characteristics in predicting overall survival (OS) and to develop a risk classification for CRPC patients treated with docetaxel-based chemotherapy. This study included 79 patients with CRPC treated with docetaxel. The variables, including patient characteristics at diagnosis and at the start of chemotherapy, were retrospectively collected. Prognostic factors predicting OS were analyzed using the Cox proportional hazard model. Risk stratification for overall survival was determined based on the results of multivariate analysis. PSA response ≥50 % was observed in 55 (69.6 %) of all patients, and the median OS was 22.5 months. The multivariate analysis showed that age, serum PSA level at the start of chemotherapy, and Hb were independent prognostic factors for OS. In addition, ECOG performance status (PS) and the CRP-to-albumin ratio were not significant but were considered possible predictors for OS. Risk stratification according to the number of these risk factors could effectively stratify CRPC patients treated with docetaxel in terms of OS. Age, serum PSA level at the start of chemotherapy, and Hb were identified as independent prognostic factors of OS. ECOG PS and the CRP-to-albumin ratio were not significant, but were considered possible predictors for OS in Japanese CRPC patients treated with docetaxel. Risk stratification based on these factors could be helpful for estimating overall survival.
Predicting Brain Metastasis in Breast Cancer Patients: Stage Versus Biology.
Azim, Hamdy A; Abdel-Malek, Raafat; Kassem, Loay
2018-04-01
Brain metastasis (BM) is a life-threatening event in breast cancer patients. Identifying patients at a high risk for BM can help to adopt screening programs and test preventive interventions. We tried to identify the incidence of BM in different stages and subtypes of breast cancer. We reviewed the clinical records of 2193 consecutive breast cancer patients who presented between January 1999 and December 2010. We explored the incidence of BM in relation to standard clinicopathological factors, and determined the cumulative risk of BM according to the disease stage and phenotype. Of the 2193 included women, 160 (7.3%) developed BM at a median follow-up of 5.8 years. Age younger than 60 years (P = .015), larger tumors (P = .004), lymph node (LN) positivity (P < .001), high tumor grade (P = .012), and HER2 positivity (P < .001) were associated with higher incidence of BM in the whole population. In patients who presented with locoregional disease, 3 factors independently predicted BM: large tumors (hazard ratio [HR], 3.60; 95% confidence interval [CI], 1.54-8.38; P = .003), axillary LN metastasis (HR, 4.03; 95% CI, 1.91-8.52; P < .001), and HER2 positivity (HR, 1.89; 95% CI, 1.0-3.41; P = .049). A Brain Relapse Index was formulated using those 3 factors, with 5-year cumulative incidence of BM of 19.2% in those having the 2 or 3 risk factors versus 2.5% in those with no or 1 risk factor (P < .001). In metastatic patients, 3 factors were associated with higher risk of BM: HER2 positivity (P = .007), shorter relapse-free interval (P < .001), and lung metastasis (P < .001). Disease stage and biological subtypes predict the risk for BM and subsequent treatment outcome. Copyright © 2017 Elsevier Inc. All rights reserved.
Risk factors predict post-traumatic stress disorder differently in men and women
Christiansen, Dorte M; Elklit, Ask
2008-01-01
Background About twice as many women as men develop post-traumatic stress disorder (PTSD), even though men as a group are exposed to more traumatic events. Exposure to different trauma types does not sufficiently explain why women are more vulnerable. Methods The present work examines the effect of age, previous trauma, negative affectivity (NA), anxiety, depression, persistent dissociation, and social support on PTSD separately in men and women. Subjects were exposed to either a series of explosions in a firework factory near a residential area or to a high school stabbing incident. Results Some gender differences were found in the predictive power of well known risk factors for PTSD. Anxiety predicted PTSD in men, but not in women, whereas the opposite was found for depression. Dissociation was a better predictor for PTSD in women than in men in the explosion sample but not in the stabbing sample. Initially, NA predicted PTSD better in women than men in the explosion sample, but when compared only to other significant risk factors, it significantly predicted PTSD for both men and women in both studies. Previous traumatic events and age did not significantly predict PTSD in either gender. Conclusion Gender differences in the predictive value of social support on PTSD appear to be very complex, and no clear conclusions can be made based on the two studies included in this article. PMID:19017412
Woo, Se Joon; Ahn, Jeeyun; Morrison, Margaux A; Ahn, So Yeon; Lee, Jaebong; Kim, Ki Woong; DeAngelis, Margaret M; Park, Kyu Hyung
2015-01-01
To investigate the association of genetic and environmental factors, and their interactions in Korean patients with exudative age-related macular degeneration (AMD). A total of 314 robustly characterized exudative AMD patients, including 111 PCV (polypoidal choroidal vasculopathy) and 154 typical choroidal neovascularization (CNV), and 395 control subjects without any evidence of AMD were enrolled. Full ophthalmologic examinations including fluorescein angiography (FA), indocyanine green angiography (ICG) and optical coherence tomography (OCT) were done, according to which patients were divided into either PCV or typical CNV. Standardized questionnaires were used to collect information regarding underlying systemic diseases, dietary habits, smoking history and body mass index (BMI). A total of 86 SNPs from 31 candidate genes were analyzed. Genotype association and logistic regression analyses were done and stepwise regression models to best predict disease for each AMD subtype were constructed. Age, spherical equivalent, myopia, and ever smoking were associated with exudative AMD. Age, hypertension, hyperlipidemia, spherical equivalent, and myopia were risk factors for typical CNV, while increased education and ever smoking were significantly associated with PCV (p<.05 for all). Four SNPs, ARMS2/HTRA1 rs10490924, rs11200638, and rs2736911, and CFH rs800292, showed association with exudative AMD. Two of these SNPs, ARMS2/HTRA1 rs10490924 and rs11200638, showed significant association with typical CNV and PCV specifically. There were no significant interactions between environmental and genetic factors. The most predictive disease model for exudative AMD included age, spherical equivalent, smoking, CFH rs800292, and ARMS2 rs10490924 while that for typical CNV included age, hyperlipidemia, spherical equivalent, and ARMS2 rs10490924. Smoking, spherical equivalent, and ARMS2 rs10490924 were the most predictive variables for PCV. When comparing PCV cases to CNV cases, age, BMI, and education were the most predictive risk factors of PCV. Only one locus, the ARMS2/HTRA1 was a significant genetic risk factor for Korean exudative AMD, including its subtypes, PCV and typical CNV. Stepwise regression revealed that CFH was important to risk of exudative AMD in general but not to any specific subtype. While increased education was a unique risk factor to PCV when compared to CNV, this association was independent of refractive error in this homogenous population from South Korea. No significant interactions between environmental and genetic risk factors were observed.
A risk scoring system for prediction of haemorrhagic stroke.
Zodpey, S P; Tiwari, R R
2005-01-01
The present pair-matched case control study was carried out at Government Medical College Hospital, Nagpur, India, a tertiary care hospital with the objective to devise and validate a risk scoring system for prediction of hemorrhagic stroke. The study consisted of 166 hospitalized CT scan proved cases of hemorrhagic stroke (ICD 9, 431-432), and a age and sex matched control per case. The controls were selected from patients who attended the study hospital for conditions other than stroke. On conditional multiple logistic regression five risk factors- hypertension (OR = 1.9. 95% Cl = 1.5-2.5). raised scrum total cholesterol (OR = 2.3, 95% Cl = 1.1-4.9). use of anticoagulants and antiplatelet agents (OR = 3.4, 95% Cl =1.1-10.4). past history of transient ischaemic attack (OR = 8.4, 95% Cl = 2.1- 33.6) and alcohol intake (OR = 2.1, 95% Cl = 1.3-3.6) were significant. These factors were ascribed statistical weights (based on regression coefficients) of 6, 8, 12, 21 and 8 respectively. The nonsignificant factors (diabetes mellitus, physical inactivity, obesity, smoking, type A personality, history of claudication, family history of stroke, history of cardiac diseases and oral contraceptive use in females) were not included in the development of scoring system. ROC curve suggested a total score of 21 to be the best cut-off for predicting haemorrhag stroke. At this cut-off the sensitivity, specificity, positive predictivity and Cohen's kappa were 0.74, 0.74, 0.74 and 0.48 respectively. The overall predictive accuracy of this additive risk scoring system (area under ROC curve by Wilcoxon statistic) was 0.79 (95% Cl = 0.73-0.84). Thus to conclude, if substantiated by further validation, this scorincy system can be used to predict haemorrhagic stroke, thereby helping to devise effective risk factor intervention strategy.
Population impact of familial and environmental risk factors for schizophrenia: a nationwide study.
Sørensen, Holger J; Nielsen, Philip R; Pedersen, Carsten B; Benros, Michael E; Nordentoft, Merete; Mortensen, Preben B
2014-03-01
Although several studies have examined the relative contributions of familial and environmental risk factors for schizophrenia, few have additionally examined the predictive power on the individual level and simultaneously examined the population impact associated with a wide range of familial and environmental risk factors. The authors present rate ratios (IRR), population-attributable risks (PAR) and sex-specific cumulative incidences of the following risk factors: parental history of mental illness, urban place of birth, advanced paternal age, parental loss and immigration status. We established a population-based cohort of 2,486,646million persons born in Denmark between 1 January 1955 and 31 December 1993 using Danish registers. We found that PAR associated with urban birth was 11.73%; PAR associated with one, respectively 2, parent(s) with schizophrenia was 2.67% and 0.12%. PAR associated with second-generation immigration was 0.70%. Highest cumulative incidence (CI=20.23%; 95% CI=18.10-22.62) was found in male offspring of 2 parents with schizophrenia. Cumulative incidences for male offspring or female offspring of a parent with schizophrenia were 9.53% (95% CI=7.71-11.79), and 4.89%, (95% CI 4.50-5.31). The study showed that risk factors with highest predictive power on the individual level have a relatively low population impact. The challenge in future studies with direct genetic data is to examine gene-environmental interactions that can move research beyond current approaches and seek to achieve higher predictive power on the individual level and higher population impact. Copyright © 2014 Elsevier B.V. All rights reserved.
Van Schaik, Fiona D M; Verhagen, Marc A M T; Siersema, Peter D; Oldenburg, Bas
2008-09-01
Osteopenia and osteoporosis are frequently encountered in patients with Inflammatory Bowel Disease (IBD). Our aims were to evaluate the actual practice of screening for low bone mineral density (BMD) by dual energy X-ray absorptiometry (DEXA), to determine the prevalence of low BMD and to investigate the risk factors associated with a low BMD in the IBD population of a regional Dutch hospital. A retrospective chart review was performed in 474 patients (259 with ulcerative colitis, 210 with Crohn's disease and 5 with indeterminate colitis). DEXA results and potential predictive factors of low BMD were documented. Predictive factors of low BMD were assessed by logistic regression. DEXA was performed in 168 IBD patients (35.4%). A low BMD (T-score<-1) was present in 64.3%. Osteoporosis (T-score<-2.5) was found in 23.8%. Low BMI, older age at the moment of diagnosis and male gender were found to be predictive factors of low BMD. For patients with osteoporosis, disease duration was an additional predictive factor. After subgroup analysis predictive factors were found to be the same in patients with Crohn's disease. The prevalence of osteopenia and osteoporosis in IBD patients in a regional centre is as high as the prevalence rates reported from tertiary referral centres. A low BMI, an older age at the moment of diagnosis and male gender were predictive factors of low BMD. Prediction of osteoporosis and osteopenia using risk factors identified in this and previous studies is presently not feasible.
Takahara, Mitsuyoshi; Katakami, Naoto; Kaneto, Hideaki; Noguchi, Midori; Shimomura, Iichiro
2014-01-01
The aim of the current study was to develop a predictive model of insulin resistance using general health checkup data in Japanese employees with one or more metabolic risk factors. We used a database of 846 Japanese employees with one or more metabolic risk factors who underwent general health checkup and a 75-g oral glucose tolerance test (OGTT). Logistic regression models were developed to predict existing insulin resistance evaluated using the Matsuda index. The predictive performance of these models was assessed using the C statistic. The C statistics of body mass index (BMI), waist circumference and their combined use were 0.743, 0.732 and 0.749, with no significant differences. The multivariate backward selection model, in which BMI, the levels of plasma glucose, high-density lipoprotein (HDL) cholesterol, log-transformed triglycerides and log-transformed alanine aminotransferase and hypertension under treatment remained, had a C statistic of 0.816, with a significant difference compared to the combined use of BMI and waist circumference (p<0.01). The C statistic was not significantly reduced when the levels of log-transformed triglycerides and log-transformed alanine aminotransferase and hypertension under treatment were simultaneously excluded from the multivariate model (p=0.14). On the other hand, further exclusion of any of the remaining three variables significantly reduced the C statistic (all p<0.01). When predicting the presence of insulin resistance using general health checkup data in Japanese employees with metabolic risk factors, it is important to take into consideration the BMI and fasting plasma glucose and HDL cholesterol levels.
Using decision tree analysis to identify risk factors for relapse to smoking
Piper, Megan E.; Loh, Wei-Yin; Smith, Stevens S.; Japuntich, Sandra J.; Baker, Timothy B.
2010-01-01
This research used classification tree analysis and logistic regression models to identify risk factors related to short- and long-term abstinence. Baseline and cessation outcome data from two smoking cessation trials, conducted from 2001 to 2002, in two Midwestern urban areas, were analyzed. There were 928 participants (53.1% women, 81.8% white) with complete data. Both analyses suggest that relapse risk is produced by interactions of risk factors and that early and late cessation outcomes reflect different vulnerability factors. The results illustrate the dynamic nature of relapse risk and suggest the importance of efficient modeling of interactions in relapse prediction. PMID:20397871
Arane, Karen; Mendelsohn, Kerry; Mimouni, Michael; Mimouni, Francis; Koren, Yael; Simon, Dafna Brik; Bahat, Hilla; Helou, Mona Hanna; Mendelson, Amir; Hezkelo, Nofar; Glatstein, Miguel; Berkun, Yackov; Eisenstein, Eli; Aviel, Yonatan Butbul; Brik, Riva; Hashkes, Philip J; Uziel, Yosef; Harel, Liora; Amarilyo, Gil
2018-05-24
This study assessed the validity of using established Japanese risk scoring methods to predict intravenous immunoglobulin (IVIG) resistance to Kawasaki disease in Israeli children. We reviewed the medical records of 282 patients (70% male) with Kawasaki disease from six Israeli medical centres between 2004-2013. Their mean age was 2.5 years. The risk scores were calculated using the Kobayashi, Sano and Egami scoring methods and analysed to determine if a higher risk score predicted IVIG resistance in this population. Factors that predicted a lack of response to the initial IVIG dose were identified. We found that 18% did not respond to the first IVIG dose. The three scoring methods were unable to reliably predict IVIG resistance, with sensitivities of 23-32% and specificities of 67-87%. Calculating a predictive score that was specific for this population was also unsuccessful. The factors that predicted a lacked of response to the first IVIG dose included low albumin, elevated total bilirubin and ethnicity. The established risk scoring methods created for Japanese populations with Kawasaki disease were not suitable for predicting IVIG resistance in Caucasian Israeli children and we were unable to create a specific scoring method that was able to do this. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
The prevalence and risk factors for gallstone disease in taiwanese vegetarians.
Chen, Yen-Chun; Chiou, Chia; Lin, Ming-Nan; Lin, Chin-Lon
2014-01-01
Gallstone disease (GSD) and its complications are major public health issues globally. Although many community-based studies had addressed the risk factors for GSD, little is known about GSD prevalence and risk factors among Taiwanese vegetarians. This study included 1721 vegetarians who completed a questionnaire detailing their demographics, medical history, and life-styles. GSD was ascertained by ultrasonography or surgical history of cholecystectomy for GSD. The predictive probability of GSD for male and female vegetarians was estimated from the fitted model. The prevalence of GSD was 8.2% for both male and female vegetarians. The risk of GSD is similar in men and women across all age groups, and increases steadily with increasing age. For male vegetarians, age (OR: 1.04; 95% CI: 1.00-1.08) and serum total bilirubin level (OR: 2.35; 95% CI: 1.31-4.22) predict risk for GSD. For female vegetarians, age (OR: 1.03; 95% CI: 1.01-1.05), BMI (OR: 1.07; 95% CI: 1.01-1.13), and alcohol consumption (OR: 7.85; 95% CI: 1.83-33.73) are associated with GSD. GSD is not associated with type of vegetarian diet, duration of vegetarianism, low education level, physical inactivity, diabetes, coronary artery disease, cerebral vascular accident, chronic renal failure, hepatitis C virus infection, and lipid abnormalities. GSD is also not associated with age at menarche, postmenopausal status, and multiparity in female vegetarians. Risk factors useful for predicting GSD in vegetarians are (1) age and total bilirubin level in men, and (2) age, BMI, and alcohol consumption in women. Many previously identified risk factors for general population does not seem to apply to Taiwanese vegetarians.
Predictive factors for somatization in a trauma sample
2009-01-01
Background Unexplained somatic symptoms are common among trauma survivors. The relationship between trauma and somatization appears to be mediated by posttraumatic stress disorder (PTSD). However, only few studies have focused on what other psychological risk factors may predispose a trauma victim towards developing somatoform symptoms. Methods The present paper examines the predictive value of PTSD severity, dissociation, negative affectivity, depression, anxiety, and feeling incompetent on somatization in a Danish sample of 169 adult men and women who were affected by a series of explosions in a firework factory settled in a residential area. Results Negative affectivity and feelings of incompetence significantly predicted somatization, explaining 42% of the variance. PTSD was significant until negative affectivity was controlled for. Conclusion Negative affectivity and feelings of incompetence significantly predicted somatization in the trauma sample whereas dissociation, depression, and anxiety were not associated with degree of somatization. PTSD as a risk factor was mediated by negative affectivity. PMID:19126224
Don't panic: interpretation bias is predictive of new onsets of panic disorder.
Woud, Marcella L; Zhang, Xiao Chi; Becker, Eni S; McNally, Richard J; Margraf, Jürgen
2014-01-01
Psychological models of panic disorder postulate that interpretation of ambiguous material as threatening is an important maintaining factor for the disorder. However, demonstrations of whether such a bias predicts onset of panic disorder are missing. In the present study, we used data from the Dresden Prediction Study, in which a epidemiologic sample of young German women was tested at two time points approximately 17 months apart, allowing the study of biased interpretation as a potential risk factor. At time point one, participants completed an Interpretation Questionnaire including two types of ambiguous scenarios: panic-related and general threat-related. Analyses revealed that a panic-related interpretation bias predicted onset of panic disorder, even after controlling for two established risk factors: anxiety sensitivity and fear of bodily sensations. This is the first prospective study demonstrating the incremental validity of interpretation bias as a predictor of panic disorder onset. Copyright © 2013 Elsevier Ltd. All rights reserved.
C-reactive protein, fibrinogen, and cardiovascular disease prediction.
Kaptoge, Stephen; Di Angelantonio, Emanuele; Pennells, Lisa; Wood, Angela M; White, Ian R; Gao, Pei; Walker, Matthew; Thompson, Alexander; Sarwar, Nadeem; Caslake, Muriel; Butterworth, Adam S; Amouyel, Philippe; Assmann, Gerd; Bakker, Stephan J L; Barr, Elizabeth L M; Barrett-Connor, Elizabeth; Benjamin, Emelia J; Björkelund, Cecilia; Brenner, Hermann; Brunner, Eric; Clarke, Robert; Cooper, Jackie A; Cremer, Peter; Cushman, Mary; Dagenais, Gilles R; D'Agostino, Ralph B; Dankner, Rachel; Davey-Smith, George; Deeg, Dorly; Dekker, Jacqueline M; Engström, Gunnar; Folsom, Aaron R; Fowkes, F Gerry R; Gallacher, John; Gaziano, J Michael; Giampaoli, Simona; Gillum, Richard F; Hofman, Albert; Howard, Barbara V; Ingelsson, Erik; Iso, Hiroyasu; Jørgensen, Torben; Kiechl, Stefan; Kitamura, Akihiko; Kiyohara, Yutaka; Koenig, Wolfgang; Kromhout, Daan; Kuller, Lewis H; Lawlor, Debbie A; Meade, Tom W; Nissinen, Aulikki; Nordestgaard, Børge G; Onat, Altan; Panagiotakos, Demosthenes B; Psaty, Bruce M; Rodriguez, Beatriz; Rosengren, Annika; Salomaa, Veikko; Kauhanen, Jussi; Salonen, Jukka T; Shaffer, Jonathan A; Shea, Steven; Ford, Ian; Stehouwer, Coen D A; Strandberg, Timo E; Tipping, Robert W; Tosetto, Alberto; Wassertheil-Smoller, Sylvia; Wennberg, Patrik; Westendorp, Rudi G; Whincup, Peter H; Wilhelmsen, Lars; Woodward, Mark; Lowe, Gordon D O; Wareham, Nicholas J; Khaw, Kay-Tee; Sattar, Naveed; Packard, Chris J; Gudnason, Vilmundur; Ridker, Paul M; Pepys, Mark B; Thompson, Simon G; Danesh, John
2012-10-04
There is debate about the value of assessing levels of C-reactive protein (CRP) and other biomarkers of inflammation for the prediction of first cardiovascular events. We analyzed data from 52 prospective studies that included 246,669 participants without a history of cardiovascular disease to investigate the value of adding CRP or fibrinogen levels to conventional risk factors for the prediction of cardiovascular risk. We calculated measures of discrimination and reclassification during follow-up and modeled the clinical implications of initiation of statin therapy after the assessment of CRP or fibrinogen. The addition of information on high-density lipoprotein cholesterol to a prognostic model for cardiovascular disease that included age, sex, smoking status, blood pressure, history of diabetes, and total cholesterol level increased the C-index, a measure of risk discrimination, by 0.0050. The further addition to this model of information on CRP or fibrinogen increased the C-index by 0.0039 and 0.0027, respectively (P<0.001), and yielded a net reclassification improvement of 1.52% and 0.83%, respectively, for the predicted 10-year risk categories of "low" (<10%), "intermediate" (10% to <20%), and "high" (≥20%) (P<0.02 for both comparisons). We estimated that among 100,000 adults 40 years of age or older, 15,025 persons would initially be classified as being at intermediate risk for a cardiovascular event if conventional risk factors alone were used to calculate risk. Assuming that statin therapy would be initiated in accordance with Adult Treatment Panel III guidelines (i.e., for persons with a predicted risk of ≥20% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), additional targeted assessment of CRP or fibrinogen levels in the 13,199 remaining participants at intermediate risk could help prevent approximately 30 additional cardiovascular events over the course of 10 years. In a study of people without known cardiovascular disease, we estimated that under current treatment guidelines, assessment of the CRP or fibrinogen level in people at intermediate risk for a cardiovascular event could help prevent one additional event over a period of 10 years for every 400 to 500 people screened. (Funded by the British Heart Foundation and others.).
Manuel, Douglas G; Perez, Richard; Sanmartin, Claudia; Taljaard, Monica; Hennessy, Deirdre; Wilson, Kumanan; Tanuseputro, Peter; Manson, Heather; Bennett, Carol; Tuna, Meltem; Fisher, Stacey; Rosella, Laura C
2016-08-01
Behaviours such as smoking, poor diet, physical inactivity, and unhealthy alcohol consumption are leading risk factors for death. We assessed the Canadian burden attributable to these behaviours by developing, validating, and applying a multivariable predictive model for risk of all-cause death. A predictive algorithm for 5 y risk of death-the Mortality Population Risk Tool (MPoRT)-was developed and validated using the 2001 to 2008 Canadian Community Health Surveys. There were approximately 1 million person-years of follow-up and 9,900 deaths in the development and validation datasets. After validation, MPoRT was used to predict future mortality and estimate the burden of smoking, alcohol, physical inactivity, and poor diet in the presence of sociodemographic and other risk factors using the 2010 national survey (approximately 90,000 respondents). Canadian period life tables were generated using predicted risk of death from MPoRT. The burden of behavioural risk factors attributable to life expectancy was estimated using hazard ratios from the MPoRT risk model. The MPoRT 5 y mortality risk algorithms were discriminating (C-statistic: males 0.874 [95% CI: 0.867-0.881]; females 0.875 [0.868-0.882]) and well calibrated in all 58 predefined subgroups. Discrimination was maintained or improved in the validation cohorts. For the 2010 Canadian population, unhealthy behaviour attributable life expectancy lost was 6.0 years for both men and women (for men 95% CI: 5.8 to 6.3 for women 5.8 to 6.2). The Canadian life expectancy associated with health behaviour recommendations was 17.9 years (95% CI: 17.7 to 18.1) greater for people with the most favourable risk profile compared to those with the least favourable risk profile (88.2 years versus 70.3 years). Smoking, by itself, was associated with 32% to 39% of the difference in life expectancy across social groups (by education achieved or neighbourhood deprivation). Multivariable predictive algorithms such as MPoRT can be used to assess health burdens for sociodemographic groups or for small changes in population exposure to risks, thereby addressing some limitations of more commonly used measurement approaches. Unhealthy behaviours have a substantial collective burden on the life expectancy of the Canadian population.
Perez, Richard; Taljaard, Monica; Hennessy, Deirdre; Wilson, Kumanan; Tanuseputro, Peter; Bennett, Carol; Tuna, Meltem; Fisher, Stacey; Rosella, Laura C.
2016-01-01
Background Behaviours such as smoking, poor diet, physical inactivity, and unhealthy alcohol consumption are leading risk factors for death. We assessed the Canadian burden attributable to these behaviours by developing, validating, and applying a multivariable predictive model for risk of all-cause death. Methods A predictive algorithm for 5 y risk of death—the Mortality Population Risk Tool (MPoRT)—was developed and validated using the 2001 to 2008 Canadian Community Health Surveys. There were approximately 1 million person-years of follow-up and 9,900 deaths in the development and validation datasets. After validation, MPoRT was used to predict future mortality and estimate the burden of smoking, alcohol, physical inactivity, and poor diet in the presence of sociodemographic and other risk factors using the 2010 national survey (approximately 90,000 respondents). Canadian period life tables were generated using predicted risk of death from MPoRT. The burden of behavioural risk factors attributable to life expectancy was estimated using hazard ratios from the MPoRT risk model. Findings The MPoRT 5 y mortality risk algorithms were discriminating (C-statistic: males 0.874 [95% CI: 0.867–0.881]; females 0.875 [0.868–0.882]) and well calibrated in all 58 predefined subgroups. Discrimination was maintained or improved in the validation cohorts. For the 2010 Canadian population, unhealthy behaviour attributable life expectancy lost was 6.0 years for both men and women (for men 95% CI: 5.8 to 6.3 for women 5.8 to 6.2). The Canadian life expectancy associated with health behaviour recommendations was 17.9 years (95% CI: 17.7 to 18.1) greater for people with the most favourable risk profile compared to those with the least favourable risk profile (88.2 years versus 70.3 years). Smoking, by itself, was associated with 32% to 39% of the difference in life expectancy across social groups (by education achieved or neighbourhood deprivation). Conclusions Multivariable predictive algorithms such as MPoRT can be used to assess health burdens for sociodemographic groups or for small changes in population exposure to risks, thereby addressing some limitations of more commonly used measurement approaches. Unhealthy behaviours have a substantial collective burden on the life expectancy of the Canadian population. PMID:27529741
Child and adolescent risk factors that differentially predict violent versus nonviolent crime.
Kalvin, Carla B; Bierman, Karen L
2017-11-01
While most research on the development of antisocial and criminal behavior has considered nonviolent and violent crime together, some evidence points to differential risk factors for these separate types of crime. The present study explored differential risk for nonviolent and violent crime by investigating the longitudinal associations between three key child risk factors (aggression, emotion dysregulation, and social isolation) and two key adolescent risk factors (parent detachment and deviant peer affiliation) predicting violent and nonviolent crime outcomes in early adulthood. Data on 754 participants (46% African American, 50% European American, 4% other; 58% male) oversampled for aggressive-disruptive behavior were collected across three time points. Parents and teachers rated aggression, emotion dysregulation, and social isolation in fifth grade (middle childhood, age 10-11); parents and youth rated parent detachment and deviant peer affiliation in seventh and eighth grade (early adolescence, age 12-14) and arrest data were collected when participants were 22-23 years old (early adulthood). Different pathways to violent and nonviolent crime emerged. The severity of child dysfunction in late childhood, including aggression, emotion dysregulation, and social isolation, was a powerful and direct predictor of violent crime. Although child dysfunction also predicted nonviolent crime, the direct pathway accounted for half as much variance as the direct pathway to violent crime. Significant indirect pathways through adolescent socialization experiences (peer deviancy) emerged for nonviolent crime, but not for violent crime, suggesting adolescent socialization plays a more distinctive role in predicting nonviolent than violent crime. The clinical implications of these findings are discussed. © 2017 Wiley Periodicals, Inc.
Jonnagaddala, Jitendra; Liaw, Siaw-Teng; Ray, Pradeep; Kumar, Manish; Dai, Hong-Jie; Hsu, Chien-Yeh
2015-01-01
Heart disease is the leading cause of death worldwide. Therefore, assessing the risk of its occurrence is a crucial step in predicting serious cardiac events. Identifying heart disease risk factors and tracking their progression is a preliminary step in heart disease risk assessment. A large number of studies have reported the use of risk factor data collected prospectively. Electronic health record systems are a great resource of the required risk factor data. Unfortunately, most of the valuable information on risk factor data is buried in the form of unstructured clinical notes in electronic health records. In this study, we present an information extraction system to extract related information on heart disease risk factors from unstructured clinical notes using a hybrid approach. The hybrid approach employs both machine learning and rule-based clinical text mining techniques. The developed system achieved an overall microaveraged F-score of 0.8302.
Puddu, Paolo Emilio; Piras, Paolo; Menotti, Alessandro
2017-02-01
To study coronary heart disease (CHD) death versus 11 other causes of death using the cumulative incidence function (CIF) and the competing risks procedures to disentangle the differential role of risk factors for different end-points. Standard Cox and Fine-Gray models among 1712 middle-aged men were compared during 50years of follow-up. CHD death was the primary event, while deaths from 11 selected causes, mutually exclusive from the primary end-point, were considered as secondary events. Reverse solutions were also performed. We considered 10 selected risk factors. CHD death risk was the second highest among 12 mostly specific causes of death. Some risk factors were specific: serum cholesterol for CHD death whereas, systolic blood pressure, cigarette smoking and age may have a differential role in other causes of death. Application of the Fine-Gray model based on CIF enabled to dissect, at least in part, the respective role that baseline covariates may have to segregate the probabilities of two types of death in contrast from each other. They also point to the absence of contributing significance for some of the selected risk factors and this calls for a parsimonious approach in predictions. The relative rarity of competing risk challenges when defining the risk factors role at long-term needs now be corrected since we have clearly shown, with Fine-Gray model, at direct or reverse use, that comparing different end-points heavily influences the risk factor predictive capacity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Ho, Gloria Y F; Einstein, Mark H; Romney, Seymour L; Kadish, Anna S; Abadi, Maria; Mikhail, Magdy; Basu, Jayasri; Thysen, Benjamin; Reimers, Laura; Palan, Prabhudas R; Trim, Shelly; Soroudi, Nafisseh; Burk, Robert D
2011-10-01
: This study examines risk factors for persistent cervical intraepithelial neoplasia (CIN) and examines whether human papillomavirus (HPV) testing predicts persistent lesions. : Women with histologically diagnosed CIN 1 or CIN 2 (n = 206) were followed up every 3 months without treatment. Human papillomavirus genotyping, plasma levels of ascorbic acid, and red blood cell folate levels were obtained. Cervical biopsy at 12 months determined the presence of CIN. Relative risk (RR) was estimated by log-linked binomial regression models. : At 12 months, 70% of CIN 1 versus 54% of CIN 2 lesions spontaneously regressed (p < .001). Levels of folate or ascorbic acid were not associated with persistent CIN at 12 months. Compared with HPV-negative women, those with multiple HPV types (RRs ranged from 1.68 to 2.17 at each follow-up visit) or high-risk types (RRs range = 1.74-2.09) were at increased risk for persistent CIN; women with HPV-16/18 had the highest risk (RRs range = 1.91-2.21). Persistent infection with a high-risk type was also associated with persistent CIN (RRs range = 1.50-2.35). Typing for high-risk HPVs at 6 months only had a sensitivity of 46% in predicting persistence of any lesions at 12 months. : Spontaneous regression of CIN 1 and 2 occurs frequently within 12 months. Human papillomavirus infection is the major risk factor for persistent CIN. However, HPV testing cannot reliably predict persistence of any lesion.
Relationship Risks in Context: A Cumulative Risk Approach to Understanding Relationship Satisfaction
Rauer, Amy J.; Karney, Benjamin R.; Garvan, Cynthia W.; Hou, Wei
2009-01-01
Risks associated with less satisfying intimate relationships often co-occur within individuals, raising questions about approaches that consider only their independent impact. Utilizing the cumulative risk model, which acknowledges the natural covariation of risk factors, this study examined individuals in intimate relationships using the Florida Family Formation Survey (n = 2,876) and a replication sample (n = 1,048). Analyses confirmed that not only was relationship satisfaction lower among those with more risks, but the cumulative risk score was predictive above and beyond the individual risk factors. Furthermore, experiencing multiple risks exacerbated the negative associations between individual risks and relationship satisfaction, suggesting that the operation of a risk factor in a relationship is moderated by the presence or absence of other risks. PMID:19587840
Ku, Chee Wai; Allen, John C; Malhotra, Rahul; Chong, Han Chung; Tan, Nguan Soon; Østbye, Truls; Lek, Sze Min; Lie, Desiree; Tan, Thiam Chye
2015-01-01
This study seeks to establish progesterone and progesterone-induced blocking factor (PIBF) levels as predictors of subsequent completed miscarriage among women presenting with threatened miscarriage between 6 and 10 weeks of gestation. Our secondary objective was to assess the known maternal risk factors, toward development of a parsimonious and clinician-friendly risk assessment model for predicting completed miscarriage. In this article, we present a prospective cohort study of 119 patients presenting with threatened miscarriage from gestation weeks 6 to 10 at a tertiary women's hospital emergency unit in Singapore. Thirty (25.2%) women had a spontaneous miscarriage. Low progesterone and PIBF levels are similarly predictive of subsequent completed miscarriage. Study results (OR, 95% CI) showed that higher levels of progesterone (0.91, 95% CI 0.88-0.94) and PIBF (0.99, 95% CI 0.98-0.99) were associated with lower risk of miscarriage. Low progesterone level was a very strong predictor of miscarriage risk in our study despite previous concerns about its pulsatile secretion. Low serum progesterone and PIBF levels predicted spontaneous miscarriage among women presenting with threatened miscarriage between gestation weeks 6 to 10. Predictive models to calculate probability of spontaneous miscarriage based on serum progesterone, together with maternal BMI and fetal heart are proposed.
Ezeamama, Amara E; Viali, Satupaitea; Tuitele, John; McGarvey, Stephen T
2006-11-01
Early in economic development there are positive associations between socioeconomic status (SES) and cardiovascular disease (CVD) risk factors, and in the most developed market economy societies there are negative associations. The purpose of this report is to describe cross-sectional and longitudinal associations between indicators of SES and CVD risk factors in a genetically homogenous population of Samoans at different levels of economic development. At baseline 1289 participants 25-58yrs, and at 4-year follow-up, 963 participants were studied in less economically developed Samoa and in more developed American Samoa. SES was assessed by education, occupation, and material lifestyle at baseline. The CVD risk factors, obesity, type-2 diabetes and hypertension were measured at baseline and 4-year follow-up, and an index of any incident CVD risk factor at follow-up was calculated. Sex and location (Samoa and American Samoa) specific multivariable logistic regression models were used to test for relationships between SES and CVD risk factors at baseline after adjustment for age and the other SES indicators. In addition an ordinal SES index was constructed for each individual based on all three SES indicators, and used in a multivariable model to estimate the predicted probability of CVD risk factors across the SES index for the two locations. In both the models using specific SES measures and CVD risk factor outcomes, and the models using the ordinal SES index and predicted probabilities of CVD risk factors, we detected a pattern of high SES associated with: (1) elevated odds of CVD risk factors in less developed Samoa, and (2) decreased odds of CVD risk factors in more developed American Samoa. We conclude that the pattern of inverse associations between SES and CVD risk factors in Samoa and direct associations in American Samoa is attributable to the heterogeneity across the Samoas in specific exposures to social processes of economic development and the natural history of individual CVD risk factors. The findings suggest that interventions on non-communicable diseases in the Samoas must be devised based on the level of economic development, the socio-economic context of risk factor exposures, and individual characteristics such as age, sex and education level.
A Risk Prediction Model for In-hospital Mortality in Patients with Suspected Myocarditis
Xu, Duo; Zhao, Ruo-Chi; Gao, Wen-Hui; Cui, Han-Bin
2017-01-01
Background: Myocarditis is an inflammatory disease of the myocardium that may lead to cardiac death in some patients. However, little is known about the predictors of in-hospital mortality in patients with suspected myocarditis. Thus, the aim of this study was to identify the independent risk factors for in-hospital mortality in patients with suspected myocarditis by establishing a risk prediction model. Methods: A retrospective study was performed to analyze the clinical medical records of 403 consecutive patients with suspected myocarditis who were admitted to Ningbo First Hospital between January 2003 and December 2013. A total of 238 males (59%) and 165 females (41%) were enrolled in this study. We divided the above patients into two subgroups (survival and nonsurvival), according to their clinical in-hospital outcomes. To maximize the effectiveness of the prediction model, we first identified the potential risk factors for in-hospital mortality among patients with suspected myocarditis, based on data pertaining to previously established risk factors and basic patient characteristics. We subsequently established a regression model for predicting in-hospital mortality using univariate and multivariate logistic regression analyses. Finally, we identified the independent risk factors for in-hospital mortality using our risk prediction model. Results: The following prediction model for in-hospital mortality in patients with suspected myocarditis, including creatinine clearance rate (Ccr), age, ventricular tachycardia (VT), New York Heart Association (NYHA) classification, gender and cardiac troponin T (cTnT), was established in the study: P = ea/(1 + ea) (where e is the exponential function, P is the probability of in-hospital death, and a = −7.34 + 2.99 × [Ccr <60 ml/min = 1, Ccr ≥60 ml/min = 0] + 2.01 × [age ≥50 years = 1, age <50 years = 0] + 1.93 × [VT = 1, no VT = 0] + 1.39 × [NYHA ≥3 = 1, NYHA <3 = 0] + 1.25 × [male = 1, female = 0] + 1.13 × [cTnT ≥50 μg/L = 1, cTnT <50 μg/L = 0]). The area under the receiver operating characteristic curve was 0.96 (standard error = 0.015, 95% confidence interval [CI]: 0.93-0.99). The model demonstrated that a Ccr <60 ml/min (odds ratio [OR] = 19.94, 95% CI: 5.66–70.26), an age ≥50 years (OR = 7.43, 95% CI: 2.18–25.34), VT (OR = 6.89, 95% CI: 1.86–25.44), a NYHA classification ≥3 (OR = 4.03, 95% CI: 1.13–14.32), male gender (OR = 3.48, 95% CI: 0.99–12.20), and a cTnT level ≥50 μg/L (OR = 3.10, 95% CI: 0.91–10.62) were the independent risk factors for in-hospital mortality. Conclusions: A Ccr <60 ml/min, an age ≥50 years, VT, an NYHA classification ≥3, male gender, and a cTnT level ≥50 μg/L were the independent risk factors resulting from the prediction model for in-hospital mortality in patients with suspected myocarditis. In addition, sufficient life support during the early stage of the disease might improve the prognoses of patients with suspected myocarditis with multiple risk factors for in-hospital mortality. PMID:28345541
One vs. Two Breast Density Measures to Predict 5- and 10- Year Breast Cancer Risk
Kerlikowske, Karla; Gard, Charlotte C.; Sprague, Brian L.; Tice, Jeffrey A.; Miglioretti, Diana L.
2015-01-01
Background One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown. We determined if two BI-RADS density measures improves the predictive accuracy of the Breast Cancer Surveillance Consortium 5-year risk model compared to one measure. Methods We included 722,654 women aged 35–74 years with two mammograms with BI-RADS density measures on average 1.8 years apart; 13,715 developed invasive breast cancer. We used Cox regression to estimate the relative hazards of breast cancer for age, race/ethnicity, family history of breast cancer, history of breast biopsy, and one or two density measures. We developed a risk prediction model by combining these estimates with 2000–2010 Surveillance, Epidemiology, and End Results incidence and 2010 vital statistics for competing risk of death. Results The two-measure density model had marginally greater discriminatory accuracy than the one-measure model (AUC=0.640 vs. 0.635). Of 18.6% of women (134,404/722,654) who decreased density categories, 15.4% (20,741/134,404) of women whose density decreased from heterogeneously or extremely dense to a lower density category with one other risk factor had a clinically meaningful increase in 5-year risk from <1.67% with the one-density model to ≥1.67% with the two-density model. Conclusion The two-density model has similar overall discrimination to the one-density model for predicting 5-year breast cancer risk and improves risk classification for women with risk factors and a decrease in density. Impact A two-density model should be considered for women whose density decreases when calculating breast cancer risk. PMID:25824444
One versus Two Breast Density Measures to Predict 5- and 10-Year Breast Cancer Risk.
Kerlikowske, Karla; Gard, Charlotte C; Sprague, Brian L; Tice, Jeffrey A; Miglioretti, Diana L
2015-06-01
One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown. We determined whether two BI-RADS density measures improve the predictive accuracy of the Breast Cancer Surveillance Consortium 5-year risk model compared with one measure. We included 722,654 women of ages 35 to 74 years with two mammograms with BI-RADS density measures on average 1.8 years apart; 13,715 developed invasive breast cancer. We used Cox regression to estimate the relative hazards of breast cancer for age, race/ethnicity, family history of breast cancer, history of breast biopsy, and one or two density measures. We developed a risk prediction model by combining these estimates with 2000-2010 Surveillance, Epidemiology, and End Results incidence and 2010 vital statistics for competing risk of death. The two-measure density model had marginally greater discriminatory accuracy than the one-measure model (AUC, 0.640 vs. 0.635). Of 18.6% of women (134,404 of 722,654) who decreased density categories, 15.4% (20,741 of 134,404) of women whose density decreased from heterogeneously or extremely dense to a lower density category with one other risk factor had a clinically meaningful increase in 5-year risk from <1.67% with the one-density model to ≥1.67% with the two-density model. The two-density model has similar overall discrimination to the one-density model for predicting 5-year breast cancer risk and improves risk classification for women with risk factors and a decrease in density. A two-density model should be considered for women whose density decreases when calculating breast cancer risk. ©2015 American Association for Cancer Research.
Valachis, Antonios; Mamounas, Eleftherios P; Mittendorf, Elizabeth A; Hayashi, Naoki; Ishitobi, Makoto; Natoli, Clara; Fitzal, Florian; Rubio, Isabel T; Tiezzi, Daniel G; Shin, Hee-Chul; Anderson, Stewart J; Hunt, Kelly K; Matsuda, Naoko; Ohsumi, Shozo; Totomi, Athina; Nilsson, Cecilia
2018-05-03
Several studies have reported a high risk of local disease recurrence (LR) and locoregional disease recurrence (LRR) in patients with breast cancer after neoadjuvant chemotherapy (NCT) and breast-conserving therapy (BCT). The objective of the current study was to identify potential risk factors for LR and LRR after NCT and BCT. Individual patient data sets from 9 studies were pooled. The outcomes of interest were the occurrence of LR and/or LRR. A 1-stage meta-analytic approach was used. Cox proportional hazards regression models were applied to identify factors that were predictive of LR and LRR, respectively. A total of 9 studies (4125 patients) provided their data sets. The 10-year LR rate was 6.5%, whereas the 10-year LRR rate was 10.3%. Four factors were found to be associated with a higher risk of LR: 1) estrogen receptor-negative disease; 2) cN + disease; 3) a lack of pathologic complete response in axilla (pN0); and 4) pN2 to pN3 disease. The predictive score for LR determined 3 risk groups: a low-risk, intermediate-risk, and high-risk group with 10-year LR rates of 4.0%, 7.9%, and 20.4%, respectively. Two additional factors were found to be associated with an increased risk of LRR: cT3 to cT4 disease and a lack of pathologic complete response in the breast. The predictive score for LRR determined 3 risk groups; a low-risk, intermediate-risk, and high-risk group with 10-year LRR rates of 3.2%, 10.1%, and 24.1%, respectively. BCT after NCT appears to be an oncologically safe procedure for a large percentage of patients with breast cancer. Two easy-to-use clinical scores were developed that can help clinicians to identify patients at higher risk of LR and LRR after NCT and BCT and individualize the postoperative treatment plan and follow-up. Cancer 2018. © 2018 American Cancer Society. © 2018 American Cancer Society.
Nuotio, Joel; Pitkänen, Niina; Magnussen, Costan G; Buscot, Marie-Jeanne; Venäläinen, Mikko S; Elo, Laura L; Jokinen, Eero; Laitinen, Tomi; Taittonen, Leena; Hutri-Kähönen, Nina; Lyytikäinen, Leo-Pekka; Lehtimäki, Terho; Viikari, Jorma S; Juonala, Markus; Raitakari, Olli T
2017-06-01
Dyslipidemia is a major modifiable risk factor for cardiovascular disease. We examined whether the addition of novel single-nucleotide polymorphisms for blood lipid levels enhances the prediction of adult dyslipidemia in comparison to childhood lipid measures. Two thousand four hundred and twenty-two participants of the Cardiovascular Risk in Young Finns Study who had participated in 2 surveys held during childhood (in 1980 when aged 3-18 years and in 1986) and at least once in a follow-up study in adulthood (2001, 2007, and 2011) were included. We examined whether inclusion of a lipid-specific weighted genetic risk score based on 58 single-nucleotide polymorphisms for low-density lipoprotein cholesterol, 71 single-nucleotide polymorphisms for high-density lipoprotein cholesterol, and 40 single-nucleotide polymorphisms for triglycerides improved the prediction of adult dyslipidemia compared with clinical childhood risk factors. Adjusting for age, sex, body mass index, physical activity, and smoking in childhood, childhood lipid levels, and weighted genetic risk scores were associated with an increased risk of adult dyslipidemia for all lipids. Risk assessment based on 2 childhood lipid measures and the lipid-specific weighted genetic risk scores improved the accuracy of predicting adult dyslipidemia compared with the approach using only childhood lipid measures for low-density lipoprotein cholesterol (area under the receiver-operating characteristic curve 0.806 versus 0.811; P =0.01) and triglycerides (area under the receiver-operating characteristic curve 0.740 versus area under the receiver-operating characteristic curve 0.758; P <0.01). The overall net reclassification improvement and integrated discrimination improvement were significant for all outcomes. The inclusion of weighted genetic risk scores to lipid-screening programs in childhood could modestly improve the identification of those at highest risk of dyslipidemia in adulthood. © 2017 American Heart Association, Inc.
Nead, Kevin T; Zhou, Margaret J; Caceres, Roxanne Diaz; Sharp, Stephen J; Wehner, Mackenzie R; Olin, Jeffrey W; Cooke, John P; Leeper, Nicholas J
2013-03-15
Evidence-based therapies are available to reduce the risk for death from cardiovascular disease, yet many patients go untreated. Novel methods are needed to identify those at highest risk for cardiovascular death. In this study, the biomarkers β2-microglobulin, cystatin C, and C-reactive protein were measured at baseline in a cohort of participants who underwent coronary angiography. Adjusted Cox proportional-hazards models were used to determine whether the biomarkers predicted all-cause and cardiovascular mortality. Additionally, improvements in risk reclassification and discrimination were evaluated by calculating the net reclassification improvement, C-index, and integrated discrimination improvement with the addition of the biomarkers to a baseline model of risk factors for cardiovascular disease and death. During a median follow-up period of 5.6 years, there were 78 deaths among 470 participants. All biomarkers independently predicted future all-cause and cardiovascular mortality. A significant improvement in risk reclassification was observed for all-cause (net reclassification improvement 35.8%, p = 0.004) and cardiovascular (net reclassification improvement 61.9%, p = 0.008) mortality compared to the baseline risk factors model. Additionally, there was significantly increased risk discrimination with C-indexes of 0.777 (change in C-index 0.057, 95% confidence interval 0.016 to 0.097) and 0.826 (change in C-index 0.071, 95% confidence interval 0.010 to 0.133) for all-cause and cardiovascular mortality, respectively. Improvements in risk discrimination were further supported using the integrated discrimination improvement index. In conclusion, this study provides evidence that β2-microglobulin, cystatin C, and C-reactive protein predict mortality and improve risk reclassification and discrimination for a high-risk cohort of patients who undergo coronary angiography. Copyright © 2013 Elsevier Inc. All rights reserved.
Risk Factors for Suicidality among Clients with Schizophrenia.
ERIC Educational Resources Information Center
Schwartz, Robert C.; Cohen, Benjamin N.
2001-01-01
Investigates risk factors for current suicidality in clients diagnosed with schizophrenia (N=223). Results indicate that severity of depressive symptoms most strongly correlated with degree of suicidality. Younger age and recent traumatic stress each significantly predicted suicidality independent of depressive symptoms. Suggests that the…
Hypomagnesemia predicts postoperative biochemical hypocalcemia after thyroidectomy.
Luo, Han; Yang, Hongliu; Zhao, Wanjun; Wei, Tao; Su, Anping; Wang, Bin; Zhu, Jingqiang
2017-05-25
To investigate the role of magnesium in biochemical and symptomatic hypocalcemia, a retrospective study was conducted. Less-than-total thyroidectomy patients were excluded from the final analysis. Identified the risk factors of biochemical and symptomatic hypocalcemia, and investigated the correlation by logistic regression and correlation test respectively. A total of 304 patients were included in the final analysis. General incidence of hypomagnesemia was 23.36%. Logistic regression showed that gender (female) (OR = 2.238, p = 0.015) and postoperative hypomagnesemia (OR = 2.010, p = 0.017) were independent risk factors for biochemical hypocalcemia. Both Pearson and partial correlation tests indicated there was indeed significant relation between calcium and magnesium. However, relative decreasing of iPTH (>70%) (6.691, p < 0.001) and hypocalcemia (2.222, p = 0.046) were identified as risk factors of symptomatic hypocalcemia. The difference remained significant even in normoparathyroidism patients. Postoperative hypomagnesemia was independent risk factor of biochemical hypocalcemia. Relative decline of iPTH was predominating in predicting symptomatic hypocalcemia.
Running away from home: a longitudinal study of adolescent risk factors and young adult outcomes.
Tucker, Joan S; Edelen, Maria Orlando; Ellickson, Phyllis L; Klein, David J
2011-05-01
Little is known about the adolescent risk factors and young adult health-related outcomes associated with running away from home. We examined these correlates of running away using longitudinal data from 4,329 youth (48% female, 85% white) who were followed from Grade 9 to age 21. Nearly 14% of the sample reported running away in the past year at Grade 10 and/or Grade 11. Controlling for demographics and general delinquency, running away from home was predicted by lack of parental support, school disengagement, greater depressive affect, and heavier substance use at Grade 9. In turn, runaways had higher drug dependence scores and more depressive symptoms at age 21 than non-runaways, even after taking these antecedent risk factors into account. Runaway status did not predict alcohol dependence risk at age 21. Results highlight the importance of substance use and depression, both as factors propelling adolescents to run away and as important long-term consequences of running away.
Micali, N.; De Stavola, B.; Ploubidis, G.; Simonoff, E.; Treasure, J.; Field, A. E.
2015-01-01
Background Eating disorder behaviours begin in adolescence. Few longitudinal studies have investigated childhood risk and protective factors. Aims To investigate the prevalence of eating disorder behaviours and cognitions and associated childhood psychological, physical and parental risk factors among a cohort of 14-year-old children. Method Data were collected from 6140 boys and girls aged 14 years. Gender-stratified models were used to estimate prospective associations between childhood body dissatisfaction, body mass index (BMI), self-esteem, maternal eating disorder and family economic disadvantage on adolescent eating disorder behaviours and cognitions. Results Childhood body dissatisfaction strongly predicted eating disorder cognitions in girls, but only in interaction with BMI in boys. Higher self-esteem had a protective effect, particularly in boys. Maternal eating disorder predicted body dissatisfaction and weight/shape concern in adolescent girls and dieting in boys. Conclusions Risk factors for eating disorder behaviours and cognitions vary according to gender. Prevention strategies should be gender-specific and target modifiable predictors in childhood and early adolescence. PMID:26206865
Teismann, Tobias; Glaesmer, Heide; von Brachel, Ruth; Siegmann, Paula; Forkmann, Thomas
2017-10-01
The interpersonal-psychological theory of suicidal behavior posits that 2 proximal, causal, and interactive risk factors must be present for someone to desire suicide: perceived burdensomeness and thwarted belongingness. The purpose of the present study was to evaluate the predictive power of these 2 risk factors in a prospective study. A total of 231 adult outpatients (age: mean = 38.1, standard deviation = 12.3) undergoing cognitive-behavioral therapy took part in a pretreatment and a midtreatment assessment after the 10th therapy session. Perceived burdensomeness, thwarted belongingness, and the interaction between these 2 risk factors did not add incremental variance to the prediction of midtreatment suicide ideation after controlling for age, gender, depression, hopelessness, impulsivity, lifetime suicide attempts, and pretreatment suicide ideation. The best predictor of midtreatment suicide ideation was pretreatment suicide ideation. Results offer only limited support to the assumptions of the interpersonal theory of suicide. © 2017 Wiley Periodicals, Inc.
Damude, S; Wevers, K P; Murali, R; Kruijff, S; Hoekstra, H J; Bastiaannet, E
2017-09-01
Completion lymph node dissection (CLND) in sentinel node (SN)-positive melanoma patients is accompanied with morbidity, while about 80% yield no additional metastases in non-sentinel nodes (NSNs). A prediction tool for NSN involvement could be of assistance in patient selection for CLND. This study investigated which parameters predict NSN-positivity, and whether the biomarker S-100B improves the accuracy of a prediction model. Recorded clinicopathologic factors were tested for their association with NSN-positivity in 110 SN-positive patients who underwent CLND. A prediction model was developed with multivariable logistic regression, incorporating all predictive factors. Five models were compared for their predictive power by calculating the Area Under the Curve (AUC). A weighted risk score, 'S-100B Non-Sentinel Node Risk Score' (SN-SNORS), was derived for the model with the highest AUC. Besides, a nomogram was developed as visual representation. NSN-positivity was present in 24 (21.8%) patients. Sex, ulceration, number of harvested SNs, number of positive SNs, and S-100B value were independently associated with NSN-positivity. The AUC for the model including all these factors was 0.78 (95%CI 0.69-0.88). SN-SNORS was the sum of scores for the five parameters. Scores of ≤9.5, 10-11.5, and ≥12 were associated with low (0%), intermediate (21.0%) and high (43.2%) risk of NSN involvement. A prediction tool based on five parameters, including the biomarker S-100B, showed accurate risk stratification for NSN-involvement in SN-positive melanoma patients. If validated in future studies, this tool could help to identify patients with low risk for NSN-involvement. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.
Kim, Hwi Young; Lee, Dong Hyeon; Lee, Jeong-Hoon; Cho, Young Youn; Cho, Eun Ju; Yu, Su Jong; Kim, Yoon Jun; Yoon, Jung-Hwan
2018-03-20
Prediction of the outcome of sorafenib therapy using biomarkers is an unmet clinical need in patients with advanced hepatocellular carcinoma (HCC). The aim was to develop and validate a biomarker-based model for predicting sorafenib response and overall survival (OS). This prospective cohort study included 124 consecutive HCC patients (44 with disease control, 80 with progression) with Child-Pugh class A liver function, who received sorafenib. Potential serum biomarkers (namely, hepatocyte growth factor [HGF], fibroblast growth factor [FGF], vascular endothelial growth factor receptor-1, CD117, and angiopoietin-2) were tested. After identifying independent predictors of tumor response, a risk scoring system for predicting OS was developed and 3-fold internal validation was conducted. A risk scoring system was developed with six covariates: etiology, platelet count, Barcelona Clinic Liver Cancer stage, protein induced by vitamin K absence-II, HGF, and FGF. When patients were stratified into low-risk (score ≤ 5), intermediate-risk (score 6), and high-risk (score ≥ 7) groups, the model provided good discriminant functions on tumor response (concordance [c]-index, 0.884) and 12-month survival (area under the curve [AUC], 0.825). The median OS was 19.0, 11.2, and 6.1 months in the low-, intermediate-, and high-risk group, respectively (P < 0.001). In internal validation, the model maintained good discriminant functions on tumor response (c-index, 0.825) and 12-month survival (AUC, 0.803), and good calibration functions (all P > 0.05 between expected and observed values). This new model including serum FGF and HGF showed good performance in predicting the response to sorafenib and survival in patients with advanced HCC.
Cherkaoui, Imad; Sabouni, Radia; Ghali, Iraqi; Kizub, Darya; Billioux, Alexander C; Bennani, Kenza; Bourkadi, Jamal Eddine; Benmamoun, Abderrahmane; Lahlou, Ouafae; Aouad, Rajae El; Dooley, Kelly E
2014-01-01
Public tuberculosis (TB) clinics in urban Morocco. Explore risk factors for TB treatment default and develop a prediction tool. Assess consequences of default, specifically risk for transmission or development of drug resistance. Case-control study comparing patients who defaulted from TB treatment and patients who completed it using quantitative methods and open-ended questions. Results were interpreted in light of health professionals' perspectives from a parallel study. A predictive model and simple tool to identify patients at high risk of default were developed. Sputum from cases with pulmonary TB was collected for smear and drug susceptibility testing. 91 cases and 186 controls enrolled. Independent risk factors for default included current smoking, retreatment, work interference with adherence, daily directly observed therapy, side effects, quick symptom resolution, and not knowing one's treatment duration. Age >50 years, never smoking, and having friends who knew one's diagnosis were protective. A simple scoring tool incorporating these factors was 82.4% sensitive and 87.6% specific for predicting default in this population. Clinicians and patients described additional contributors to default and suggested locally-relevant intervention targets. Among 89 cases with pulmonary TB, 71% had sputum that was smear positive for TB. Drug resistance was rare. The causes of default from TB treatment were explored through synthesis of qualitative and quantitative data from patients and health professionals. A scoring tool with high sensitivity and specificity to predict default was developed. Prospective evaluation of this tool coupled with targeted interventions based on our findings is warranted. Of note, the risk of TB transmission from patients who default treatment to others is likely to be high. The commonly-feared risk of drug resistance, though, may be low; a larger study is required to confirm these findings.
Simple Scoring System to Predict In-Hospital Mortality After Surgery for Infective Endocarditis.
Gatti, Giuseppe; Perrotti, Andrea; Obadia, Jean-François; Duval, Xavier; Iung, Bernard; Alla, François; Chirouze, Catherine; Selton-Suty, Christine; Hoen, Bruno; Sinagra, Gianfranco; Delahaye, François; Tattevin, Pierre; Le Moing, Vincent; Pappalardo, Aniello; Chocron, Sidney
2017-07-20
Aspecific scoring systems are used to predict the risk of death postsurgery in patients with infective endocarditis (IE). The purpose of the present study was both to analyze the risk factors for in-hospital death, which complicates surgery for IE, and to create a mortality risk score based on the results of this analysis. Outcomes of 361 consecutive patients (mean age, 59.1±15.4 years) who had undergone surgery for IE in 8 European centers of cardiac surgery were recorded prospectively, and a risk factor analysis (multivariable logistic regression) for in-hospital death was performed. The discriminatory power of a new predictive scoring system was assessed with the receiver operating characteristic curve analysis. Score validation procedures were carried out. Fifty-six (15.5%) patients died postsurgery. BMI >27 kg/m 2 (odds ratio [OR], 1.79; P =0.049), estimated glomerular filtration rate <50 mL/min (OR, 3.52; P <0.0001), New York Heart Association class IV (OR, 2.11; P =0.024), systolic pulmonary artery pressure >55 mm Hg (OR, 1.78; P =0.032), and critical state (OR, 2.37; P =0.017) were independent predictors of in-hospital death. A scoring system was devised to predict in-hospital death postsurgery for IE (area under the receiver operating characteristic curve, 0.780; 95% CI, 0.734-0.822). The score performed better than 5 of 6 scoring systems for in-hospital death after cardiac surgery that were considered. A simple scoring system based on risk factors for in-hospital death was specifically created to predict mortality risk postsurgery in patients with IE. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Palma, David A., E-mail: david.palma@uwo.ca; Senan, Suresh; Tsujino, Kayoko
2013-02-01
Background: Radiation pneumonitis is a dose-limiting toxicity for patients undergoing concurrent chemoradiation therapy (CCRT) for non-small cell lung cancer (NSCLC). We performed an individual patient data meta-analysis to determine factors predictive of clinically significant pneumonitis. Methods and Materials: After a systematic review of the literature, data were obtained on 836 patients who underwent CCRT in Europe, North America, and Asia. Patients were randomly divided into training and validation sets (two-thirds vs one-third of patients). Factors predictive of symptomatic pneumonitis (grade {>=}2 by 1 of several scoring systems) or fatal pneumonitis were evaluated using logistic regression. Recursive partitioning analysis (RPA) wasmore » used to define risk groups. Results: The median radiation therapy dose was 60 Gy, and the median follow-up time was 2.3 years. Most patients received concurrent cisplatin/etoposide (38%) or carboplatin/paclitaxel (26%). The overall rate of symptomatic pneumonitis was 29.8% (n=249), with fatal pneumonitis in 1.9% (n=16). In the training set, factors predictive of symptomatic pneumonitis were lung volume receiving {>=}20 Gy (V{sub 20}) (odds ratio [OR] 1.03 per 1% increase, P=.008), and carboplatin/paclitaxel chemotherapy (OR 3.33, P<.001), with a trend for age (OR 1.24 per decade, P=.09); the model remained predictive in the validation set with good discrimination in both datasets (c-statistic >0.65). On RPA, the highest risk of pneumonitis (>50%) was in patients >65 years of age receiving carboplatin/paclitaxel. Predictors of fatal pneumonitis were daily dose >2 Gy, V{sub 20}, and lower-lobe tumor location. Conclusions: Several treatment-related risk factors predict the development of symptomatic pneumonitis, and elderly patients who undergo CCRT with carboplatin-paclitaxel chemotherapy are at highest risk. Fatal pneumonitis, although uncommon, is related to dosimetric factors and tumor location.« less
Van Hulst, Andraea; Roy-Gagnon, Marie-Hélène; Gauvin, Lise; Kestens, Yan; Henderson, Mélanie; Barnett, Tracie A
2015-02-15
Few studies consider how risk factors within multiple levels of influence operate synergistically to determine childhood obesity. We used recursive partitioning analysis to identify unique combinations of individual, familial, and neighborhood factors that best predict obesity in children, and tested whether these predict 2-year changes in body mass index (BMI). Data were collected in 2005-2008 and in 2008-2011 for 512 Quebec youth (8-10 years at baseline) with a history of parental obesity (QUALITY study). CDC age- and sex-specific BMI percentiles were computed and children were considered obese if their BMI was ≥95th percentile. Individual (physical activity and sugar-sweetened beverage intake), familial (household socioeconomic status and measures of parental obesity including both BMI and waist circumference), and neighborhood (disadvantage, prestige, and presence of parks, convenience stores, and fast food restaurants) factors were examined. Recursive partitioning, a method that generates a classification tree predicting obesity based on combined exposure to a series of variables, was used. Associations between resulting varying risk group membership and BMI percentile at baseline and 2-year follow up were examined using linear regression. Recursive partitioning yielded 7 subgroups with a prevalence of obesity equal to 8%, 11%, 26%, 28%, 41%, 60%, and 63%, respectively. The 2 highest risk subgroups comprised i) children not meeting physical activity guidelines, with at least one BMI-defined obese parent and 2 abdominally obese parents, living in disadvantaged neighborhoods without parks and, ii) children with these characteristics, except with access to ≥1 park and with access to ≥1 convenience store. Group membership was strongly associated with BMI at baseline, but did not systematically predict change in BMI. Findings support the notion that obesity is predicted by multiple factors in different settings and provide some indications of potentially obesogenic environments. Alternate group definitions as well as longer duration of follow up should be investigated to predict change in obesity.
Chen, Ji-Kang; Avi Astor, Ron
2010-08-01
The current study explores whether theorized risk factors in Western countries can be used to predict school violence perpetration in an Asian cultural context. The study examines the associations between risk factors and school violence perpetration in Taiwan. Data were obtained from a nationally representative sample of 14,022 students from elementary to high school (Grades 4 to 12) across Taiwan. The analysis reported in this study focuses on only junior high school students (Grades 7 to 9, N = 3,058). The results of a regression analysis show that gender, age, direct victimization, witness victimization, alcohol use, smoking, anger traits, lack of impulse control, attitudes toward violence, poor quality of student-teacher relationships, and involvement with at-risk peers were significantly associated with school violence in Taiwan. The overall results suggest strong similarities in risk factors found in the West and school violence in Taiwan. They therefore point toward using similar strategies developed in the West to enhance students' positive experiences in their personal, family, and school lives to decrease school violence.
Risk assessment and management to prevent preterm birth.
Koullali, B; Oudijk, M A; Nijman, T A J; Mol, B W J; Pajkrt, E
2016-04-01
Preterm birth is the most important cause of neonatal mortality and morbidity worldwide. In this review, we review potential risk factors associated with preterm birth and the subsequent management to prevent preterm birth in low and high risk women with a singleton or multiple pregnancy. A history of preterm birth is considered the most important risk factor for preterm birth in subsequent pregnancy. General risk factors with a much lower impact include ethnicity, low socio-economic status, maternal weight, smoking, and periodontal status. Pregnancy-related characteristics, including bacterial vaginosis and asymptomatic bacteriuria, appear to be of limited value in the prediction of preterm birth. By contrast, a mid-pregnancy cervical length measurement is independently associated with preterm birth and could be used to identify women at risk of a premature delivery. A fetal fibronectin test may be of additional value in the prediction of preterm birth. The most effective methods to prevent preterm birth depend on the obstetric history, which makes the identification of women at risk of preterm birth an important task for clinical care providers. Copyright © 2016 Elsevier Ltd. All rights reserved.
Anxiety sensitivity cognitive concerns predict suicide risk.
Oglesby, Mary Elizabeth; Capron, Daniel William; Raines, Amanda Medley; Schmidt, Norman Bradley
2015-03-30
Anxiety sensitivity (AS) cognitive concerns, which reflects fears of mental incapacitation, have been previously associated with suicidal ideation and behavior. The first study aim was to replicate and extend upon previous research by investigating whether AS cognitive concerns can discriminate between those at low risk versus high risk for suicidal behavior. Secondly, we aimed to test the incremental predictive power of AS cognitive concerns above and beyond known suicide risk factors (i.e., thwarted belongingness and insomnia). The sample consisted of 106 individuals (75% meeting current criteria for an Axis I disorder) recruited from the community. Results revealed that AS cognitive concerns were a robust predictor of elevated suicide risk after covarying for negative affect, whereas AS social and physical concerns were not. Those with high, relative to low, AS cognitive scores were 3.67 times more likely to be in the high suicide risk group. Moreover, AS cognitive concerns significantly predicted elevated suicide risk above and beyond relevant suicide risk factors. Results of this study add to a growing body of the literature demonstrating a relationship between AS cognitive concerns and increased suicidality. Incorporating AS cognitive concerns amelioration protocols into existing interventions for suicidal behavior may be beneficial. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Kälsch, Hagen; Lehmann, Nils; Mahabadi, Amir A; Bauer, Marcus; Kara, Kaffer; Hüppe, Patricia; Moebus, Susanne; Möhlenkamp, Stefan; Dragano, Nico; Schmermund, Axel; Stang, Andreas; Jöckel, Karl-Heinz; Erbel, Raimund
2014-06-01
Aortic valve calcification (AVC) is considered a manifestation of atherosclerosis. In this study, we investigated whether AVC adds to cardiovascular risk prediction beyond Framingham risk factors and coronary artery calcification (CAC). A total of 3944 subjects from the population based Heinz Nixdorf Recall Study (59.3±7.7 years; 53% females) were evaluated for coronary events, stroke, and cardiovascular disease (CVD) events (including all plus CV death) over 9.1±1.9 years. CT scans were performed to quantify AVC. Cox proportional hazards regressions and Harrell's C were used to examine AVC as event predictor in addition to risk factors and CAC. During follow-up, 138 (3.5%) subjects experienced coronary events, 101 (2.6%) had a stroke, and 257 (6.5%) experienced CVD events. In subjects with AVC>0 versus AVC=0 the incidence of coronary events was 8.0% versus 3.0% (p<0.001) and the incidence of CVD events was 13.0% versus 5.7% (p<0.001). The frequency of events increased significantly with increasing AVC scores (p<0.001). After adjustment for Framingham risk factors, high AVC scores (3rd tertile) remained independently associated with coronary events (HR 2.21, 95% CI 1.28 to 3.81) and CVD events (HR 1.67, 95% CI 1.08 to 2.58). After further adjustment for CAC score, HRs were attenuated (coronary events 1.55, 95% CI 0.89 to 2.69; CVD events 1.29, 95% CI 0.83 to 2.00). When adding AVC to the model containing traditional risk factors and CAC, Harrell's C indices did not increase for coronary events (from 0.744 to 0.744) or CVD events (from 0.759 to 0.759). AVC is associated with incident coronary and CVD events independent of Framingham risk factors. However, AVC fails to improve cardiovascular event prediction over Framingham risk factors and CAC. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Predictive factors for intrauterine growth restriction.
Albu, A R; Anca, A F; Horhoianu, V V; Horhoianu, I A
2014-06-15
Reduced fetal growth is seen in about 10% of the pregnancies but only a minority has a pathological background and is known as intrauterine growth restriction or fetal growth restriction (IUGR / FGR). Increased fetal and neonatal mortality and morbidity as well as adult pathologic conditions are often associated to IUGR. Risk factors for IUGR are easy to assess but have poor predictive value. For the diagnostic purpose, biochemical serum markers, ultrasound and Doppler study of uterine and spiral arteries, placental volume and vascularization, first trimester growth pattern are object of assessment today. Modern evaluations propose combined algorithms using these strategies, all with the goal of a better prediction of risk pregnancies.
Buckner, Julia D.; Schmidt, Norman B.
2009-01-01
Increasing evidence indicates that social anxiety may be a premorbid risk factor for alcohol use disorders (AUD). The aim of this study was to replicate and extend previous work examining whether social anxiety is a risk factor for AUD by evaluating both the temporal antecedence and non-spuriousness of this relationship. We also examined whether social anxiety first-order factors (social interaction anxiety, observation anxieties) served as specific predictors of AUD. A non-referred sample of 404 psychologically healthy young adults (i.e. free from current or past Axis I psychopathology) was prospectively followed over approximately two years. Social anxiety (but not depression or trait anxiety) at baseline significantly predicted subsequent AUD onset. The relationship between social anxiety and AUD remained even after controlling for relevant variables (gender, depression, trait anxiety). Further, social anxiety first-order factors differentially predicted AUD onset, such that observation anxieties (but not social interaction anxiety) were prospectively linked to AUD onset. This study provides further support that social anxiety (and fear of scrutiny specifically) appears to serve as an important and potentially specific AUD-related variable that deserves serious attention as a potential vulnerability factor. PMID:18547587
Gach, Emily J; Ip, Ka I; Sameroff, Arnold J; Olson, Sheryl L
2018-02-01
Multiple environmental risk factors in early childhood predict a broad range of adverse developmental outcomes. However, most prior longitudinal research has not illuminated explanatory mechanisms. Our main goals were to examine predictive associations between cumulative ecological risk factors in early childhood and children's later externalizing problems and to determine whether these associations were explained by variations in parenting quality. Participants were 241 children (118 girls) at risk for school-age conduct problems and their parents and teachers. Children were approximately 3 years old at Time 1 (T1) and 10 years old at Time 2 (T2). Reports of contextual risk at T1 were used to develop a cumulative risk index consisting of 6 singular risk variables from 3 ecological levels: social resources (low income; social isolation), family resources (marital aggression; poor total family functioning), and maternal resources (single parent status; poor maternal mental health). At T1, parenting variables were measured (corporal punishment, warm responsiveness, maternal efficacy, and negative perceptions of child behavior). At T2, mothers, fathers, and teachers reported child externalizing problems. Johnson's relative weight analysis revealed that the cumulative risk index was a more powerful predictor of age 10 years externalizing behavior than any of the singular contextual risk variables. Adverse parenting mediated the effects of cumulative risk on later child externalizing problems. Our findings have significant implications for understanding long-term effects of multiple contextual risk factors present in early childhood and for the implementation of positive parenting interventions early on. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Kondalsamy-Chennakesavan, Srinivas; Bouman, Chantal; De Jong, Suzanne; Sanday, Karen; Nicklin, Jim; Land, Russell; Obermair, Andreas
2009-12-01
Advanced gynecological surgery undertaken in a specialized gynecologic oncology unit may be associated with significant perioperative morbidity. Validated risk prediction models are available for general surgical specialties but currently not for gynecological cancer surgery. The objective of this study was to evaluate risk factors for adverse events (AEs) of patients treated for suspected or proven gynecological cancer and to develop a clinical risk score (RS) to predict such AEs. AEs were prospectively recorded and matched with demographical, clinical and histopathological data on 369 patients who had an abdominal or laparoscopic procedure for proven or suspected gynecological cancer at a tertiary gynecological cancer center. Stepwise multiple logistic regression was used to determine the best predictors of AEs. For the risk score (RS), the coefficients from the model were scaled using a factor of 2 and rounded to the nearest integer to derive the risk points. Sum of all the risk points form the RS. Ninety-five patients (25.8%) had at least one AE. Twenty-nine (7.9%) and 77 (20.9%) patients experienced intra- and postoperative AEs respectively with 11 patients (3.0%) experiencing both. The independent predictors for any AE were complexity of the surgical procedure, elevated SGOT (serum glutamic oxaloacetic transaminase, > or /=35 U/L), higher ASA scores and overweight. The risk score can vary from 0 to 14. The risk for developing any AE is described by the formula 100 / (1 + e((3.697 - (RS /2)))). RS allows for quantification of the risk for AEs. Risk factors are generally not modifiable with the possible exception of obesity.
Discrimination of health risk by combined body mass index and waist circumference.
Ardern, Christopher I; Katzmarzyk, Peter T; Janssen, Ian; Ross, Robert
2003-01-01
NIH Clinical Guidelines (1998) recommend the measurement of waist circumference (WC, centimeters) within body mass index (BMI, kilograms per square meter) categories as a screening tool for increased health risk. The Canada Heart Health Surveys (1986 through 1992) were used to describe the prevalence of the metabolic syndrome in Canada and to test the use of the NIH guidelines for predicting metabolic risk factors. The sample included 7981 participants ages 20 to 74 years who had complete data for WC, BMI, high-density lipoprotein-cholesterol, triglycerides, diabetic status, and systolic and diastolic blood pressures. National Cholesterol Education Program Adult Treatment Panel III risk categories were used to identify the metabolic syndrome and associated risk factors. Logistic regression was used to test the hypothesis that WC improves the prediction of the metabolic syndrome, within overweight (25 to 29.9 kg/m(2)) and obese I (30 to 34.9 kg/m(2)) BMI categories. The prevalence of the metabolic syndrome was 17.0% in men and 13.2% in women. The odds ratios (OR) for the prediction of the metabolic syndrome were elevated in overweight [OR, 1.85; 95% confidence interval (95%CI), 1.02 to 3.35] and obese (OR, 2.35; 95%CI, 1.25 to 4.42) women with a high WC compared with overweight and obese women with a low WC, respectively. On the other hand, WC was not predictive of the metabolic syndrome or component risk factors in men, within BMI categories. In women already at increased health risk because of an elevated BMI, the additional measurement of WC may help identify cardiovascular risk.
Franklyn-Miller, Andrew; Bilzon, James; Wilson, Cassie; McCrory, Paul
2014-03-01
Injury in initial military training is common with incidences from 25 to 65% of recruits sustaining musculoskeletal injury. Risk factors for injury include extrinsic factors such as rapid onset of high volume training, but intrinsic factors such as lower limb biomechanics and foot type. Prediction of injury would allow more effective training delivery, reduce manpower wastage and improve duty of care to individuals by addressing potential interventions. Plantar pressure interpretation of footfall has been shown to reflect biomechanical intrinsic abnormality although no quantifiable method of risk stratification exists. To identify if pressure plate assessment of walking gait is predictive of injury in a military population. 200 male subjects commencing Naval Officer training were assessed by plantar pressure plate recording, of foot contact pressures. A software interpretation, D3D™, stratified the interpretation to measure 4 specific areas of potential correction. Participants were graded as to high, medium and low risk of injury and subsequently followed up for injury through their basic training. Seventy two percent of all injuries were attributed to subjects in the high and medium risk of injury as defined by the risk categorization. 47% of all injuries were sustained in the high-risk group. Participants categorized in the high-risk group for injury were significantly more likely to sustain injury than in medium or low groups (p<0.001, OR 5.28 with 95% CI 2.88, 9.70). Plantar pressure assessment of risk for overuse lower limb injury can be predictive of sustaining an overuse injury in a controlled training environment. Copyright © 2013 Elsevier Ltd. All rights reserved.
Yu, Ruby; Leung, Jason; Woo, Jean
2014-08-01
We examined whether sarcopenia is predictive of incident fractures among older men, whether the inclusion of sarcopenia in models adds any incremental value to bone mineral density (BMD), and whether sarcopenia is associated with a higher risk of fractures in elderly with osteoporosis. A cohort of 2000 community-dwelling men aged ≥65 years were examined for which detailed information regarding demographics, socioeconomic, medical history, clinical, and lifestyle factors were documented. Body composition and BMD were measured using dual energy X-ray absorptiometry. Sarcopenia was defined according to the Asian Working Group for Sarcopenia (AWGS) algorithm. Incident fractures were documented during the follow-up period from 2001 to 2013, and related to sarcopenia and its component measures using Cox proportional hazard regressions. The contribution of sarcopenia for predicting fracture risk was evaluated by receiver operating characteristic analysis, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). During an average of 11.3 years of follow-up, 226 (11.3%) men sustained at least 1 incident fracture, making the incidence of fractures 1200.6/100,000 person-years. After multivariate adjustments, sarcopenia was associated with increased fracture risk (hazard ratio [HR], 1.87, 95% confidence interval [CI], 1.26-2.79) independent of BMD and other clinical risk factors. The addition of sarcopenia did not significantly increase area under curve or IDI but significantly improved the predictive ability on fracture risk over BMD and other clinical risk factors by 5.12% (P < .05) using the NRI approach. In addition, the combination of osteoporosis and sarcopenia (sarco-osteoporosis) resulted in a significantly increased risk of fractures (HR, 3.49, 95% CI, 1.76-6.90) compared with those with normal BMD and without sarcopenia. This study confirms that sarcopenia is a predictor of fracture risk in this elderly men cohort, establishes that sarcopenia provides incremental predictive value for fractures over the integration of BMD and other clinical risk factors, and suggests that the combination of osteoporosis and sarcopenia could identify a subgroup with a particularly high fracture risk. Copyright © 2014 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.
Kim, Jin-Woo; Cha, In-Ho; Kim, Sun-Jong; Kim, Myung-Rae
2012-11-01
Mandibular third molar extraction is a commonly performed procedure and is recognized as a relatively frequent cause of inferior alveolar nerve (IAN) injury. The aim of the present study was to investigate the specific risk factors for neurosensory deficits, including age, gender, impaction depth, angulation of the third molar, and various radiographic superimposition signs. In a case-control study of patients who had undergone mandibular third molar extraction, a case group was developed of patients showing neurosensory deficits of the IAN, and a control group was formed of randomly selected patients without any neurosensory symptoms. Bivariate analyses were performed to assess the relationship between each variable and IAN injury. A multivariate logistic regression model was used to compute the odds ratios, P values, and predictive values of the radiographic superimposition signs. Of 12,842 total patients, the study group included 104 cases and 135 controls. The results indicated that older age and deeper impaction status were significant risk factors (P < .05). Darkening of the roots, deflection of the roots, narrowing of the roots, dark and bifid apexes of the roots, and narrowing of the canal were also significant risk factors. The positive predictive values ranged from 0.7% to 6.9% and the negative predictive values from 99% to 100%, with adjustment for the definitive prevalence of IAN injury (0.81%, 104/12,842 patients). However, the relatively low positive predictive value renders questionable the predictability of superimposition signs on orthopantomography. In the absence of specific radiographic signs, the risk of neurosensory deficit of the IAN could be negligible. The sensory symptoms disappeared after 6 months in 92.3% of the patients and 98.1% showed recovery after 1 year. The results of the present study have demonstrated a significant association between several risk factors and neurosensory deficits of the IAN after third molar extraction. With a case group of 104 patients, the number of subjects was significantly greater than that in previous studies, increasing the reliability of these results. Copyright © 2012 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.
Kim, Minjae; Wall, Melanie M; Li, Guohua
2016-07-01
Perioperative risk stratification is often performed using individual risk factors without consideration of the syndemic of these risk factors. We used latent class analysis (LCA) to identify the classes of comorbidities and risk factors associated with perioperative mortality in patients presenting for intraabdominal general surgery. The 2005 to 2010 American College of Surgeons National Surgical Quality Improvement Program was used to obtain a cohort of patients undergoing intraabdominal general surgery. Risk factors and comorbidities were entered into LCA models to identify the latent classes, and individuals were assigned to a class based on the highest posterior probability of class membership. Relative risk regression was used to determine the associations between the latent classes and 30-day mortality, with adjustments for procedure. A 9-class model was fit using LCA on 466,177 observations. After combining classes with similar adjusted mortality risks, 5 risk classes were obtained. Compared with the class with average mortality risk (class 4), the risk ratios (95% confidence interval) ranged from 0.020 (0.014-0.027) in the lowest risk class (class 1) to 6.75 (6.46-7.02) in the highest risk class. After adjusting for procedure and ASA physical status, the latent classes remained significantly associated with 30-day mortality. The addition of the risk class variable to a model containing ASA physical status and surgical procedure demonstrated a significant increase in the area under the receiver operator characteristic curve (0.892 vs 0.915; P < 0.0001). Latent classes of risk factors and comorbidities in patients undergoing intraabdominal surgery are predictive of 30-day mortality independent of the ASA physical status and improve risk prediction with the ASA physical status.
Gabriel, Rafael; Brotons, Carlos; Tormo, M José; Segura, Antonio; Rigo, Fernando; Elosua, Roberto; Carbayo, Julio A; Gavrila, Diana; Moral, Irene; Tuomilehto, Jaakko; Muñiz, Javier
2015-03-01
In Spain, data based on large population-based cohorts adequate to provide an accurate prediction of cardiovascular risk have been scarce. Thus, calibration of the EuroSCORE and Framingham scores has been proposed and done for our population. The aim was to develop a native risk prediction score to accurately estimate the individual cardiovascular risk in the Spanish population. Seven Spanish population-based cohorts including middle-aged and elderly participants were assembled. There were 11800 people (6387 women) representing 107915 person-years of follow-up. A total of 1214 cardiovascular events were identified, of which 633 were fatal. Cox regression analyses were conducted to examine the contributions of the different variables to the 10-year total cardiovascular risk. Age was the strongest cardiovascular risk factor. High systolic blood pressure, diabetes mellitus and smoking were strong predictive factors. The contribution of serum total cholesterol was small. Antihypertensive treatment also had a significant impact on cardiovascular risk, greater in men than in women. The model showed a good discriminative power (C-statistic=0.789 in men and C=0.816 in women). Ten-year risk estimations are displayed graphically in risk charts separately for men and women. The ERICE is a new native cardiovascular risk score for the Spanish population derived from the background and contemporaneous risk of several Spanish cohorts. The ERICE score offers the direct and reliable estimation of total cardiovascular risk, taking in consideration the effect of diabetes mellitus and cardiovascular risk factor management. The ERICE score is a practical and useful tool for clinicians to estimate the total individual cardiovascular risk in Spain. Copyright © 2014 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.
Moreno-Peral, Patricia; Luna, Juan de Dios; Marston, Louise; King, Michael; Nazareth, Irwin; Motrico, Emma; GildeGómez-Barragán, María Josefa; Torres-González, Francisco; Montón-Franco, Carmen; Sánchez-Celaya, Marta; Díaz-Barreiros, Miguel Ángel; Vicens, Catalina; Muñoz-Bravo, Carlos; Bellón, Juan Ángel
2014-01-01
Background There are no risk algorithms for the onset of anxiety syndromes at 12 months in primary care. We aimed to develop and validate internally a risk algorithm to predict the onset of anxiety syndromes at 12 months. Methods A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multilevel logistic regression and inverse probability weighting to build the risk algorithm. Our main outcome was generalized anxiety, panic and other non-specific anxiety syndromes as measured by the Primary Care Evaluation of Mental Disorders, Patient Health Questionnaire (PRIME-MD-PHQ). We recruited 3,564 adult primary care attendees without anxiety syndromes from 174 family physicians and 32 health centers in 6 Spanish provinces. Results The cumulative 12-month incidence of anxiety syndromes was 12.2%. The predictA-Spain risk algorithm included the following predictors of anxiety syndromes: province; sex (female); younger age; taking medicines for anxiety, depression or stress; worse physical and mental quality of life (SF-12); dissatisfaction with paid and unpaid work; perception of financial strain; and the interactions sex*age, sex*perception of financial strain, and age*dissatisfaction with paid work. The C-index was 0.80 (95% confidence interval = 0.78–0.83) and the Hedges' g = 1.17 (95% confidence interval = 1.04–1.29). The Copas shrinkage factor was 0.98 and calibration plots showed an accurate goodness of fit. Conclusions The predictA-Spain risk algorithm is valid to predict anxiety syndromes at 12 months. Although external validation is required, the predictA-Spain is available for use as a predictive tool in the prevention of anxiety syndromes in primary care. PMID:25184313
Brenton, Ashley; Richeimer, Steven; Sharma, Maneesh; Lee, Chee; Kantorovich, Svetlana; Blanchard, John; Meshkin, Brian
2017-01-01
Background Opioid abuse in chronic pain patients is a major public health issue, with rapidly increasing addiction rates and deaths from unintentional overdose more than quadrupling since 1999. Purpose This study seeks to determine the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm incorporating phenotypic risk factors and neuroscience-associated single-nucleotide polymorphisms (SNPs). Patients and methods The Proove Opioid Risk (POR) algorithm determines the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm incorporating phenotypic risk factors and neuroscience-associated SNPs. In a validation study with 258 subjects with diagnosed opioid use disorder (OUD) and 650 controls who reported using opioids, the POR successfully categorized patients at high and moderate risks of opioid misuse or abuse with 95.7% sensitivity. Regardless of changes in the prevalence of opioid misuse or abuse, the sensitivity of POR remained >95%. Conclusion The POR correctly stratifies patients into low-, moderate-, and high-risk categories to appropriately identify patients at need for additional guidance, monitoring, or treatment changes. PMID:28572737
The quality of risk factor screening during antenatal consultations in Niger.
Prual, A; Toure, A; Huguet, D; Laurent, Y
2000-03-01
A decade after the first International Conference on Safe Motherhood, maternal mortality remains very high in most West African countries, even in capital cities. The detection of high risk pregnancies, known as the risk approach, during antenatal consultations has been the basis of most maternal and child health programmes over the last decade. The effectiveness of antenatal care as a tool to prevent or predict obstetric complications is being questioned more and more. In addition to the scarcity of reliable data about the predictivity of most risk factors, the quality of the screening must be questioned. The goal of this study was to assess the frequency of risk factors among a sample of pregnant women attending antenatal care in Niger and to assess the quality of the screening of those risk factors. Overall, 330 pregnant women were enrolled in the study. Each woman was examined twice: the first time by a midwife, the second time by one of the authors but without knowledge of the results of the first consultation. Fifty-five percent of pregnant women had at least one risk factor, 31% had more than one. Ninety-one percent of the risk factors were detected at interview. The following risk factors were not systematically searched for by midwives: height (48.5%), blood pressure (43.6%), glycosuria (40.6%), vaginal bleeding (38.2%), oedema (37.3%), parity (17%), age (16%), previous caesarean section (15.2%), previous stillbirth (15.2%) and previous miscarriages (14.8%). This study has shown that, in Niger, the quality of screening for risk factors during antenatal consultation is poor. In the urban settings where this study took place, lack of personnel, lack of equipment, lack of time and poor compliance by women cannot be made responsible for this situation. While screening of these risk factors continues as policy, the quality of screening must be dramatically improved.
Predictive variables for mortality after acute ischemic stroke.
Carter, Angela M; Catto, Andrew J; Mansfield, Michael W; Bamford, John M; Grant, Peter J
2007-06-01
Stroke is a major healthcare issue worldwide with an incidence comparable to coronary events, highlighting the importance of understanding risk factors for stroke and subsequent mortality. In the present study, we determined long-term (all-cause) mortality in 545 patients with ischemic stroke compared with a cohort of 330 age-matched healthy control subjects followed up for a median of 7.4 years. We assessed the effect of selected demographic, clinical, biochemical, hematologic, and hemostatic factors on mortality in patients with ischemic stroke. Stroke subtype was classified according to the Oxfordshire Community Stroke Project criteria. Patients who died 30 days or less after the acute event (n=32) were excluded from analyses because this outcome is considered to be directly attributable to the acute event. Patients with ischemic stroke were at more than 3-fold increased risk of death compared with the age-matched control cohort. In multivariate analyses, age, stroke subtype, atrial fibrillation, and previous stroke/transient ischemic attack were predictive of mortality in patients with ischemic stroke. Albumin and creatinine and the hemostatic factors von Willebrand factor and beta-thromboglobulin were also predictive of mortality in patients with ischemic stroke after accounting for demographic and clinical variables. The results indicate that subjects with acute ischemic stroke are at increased risk of all-cause mortality. Advancing age, large-vessel stroke, atrial fibrillation, and previous stroke/transient ischemic attack predict mortality; and analysis of albumin, creatinine, von Willebrand factor, and beta-thromboglobulin will aid in the identification of patients at increased risk of death after stroke.
Jackson, Todd; Chen, Hong
2015-10-01
Body surveillance and body shame are features of objectified body consciousness (OBC) that have been linked to disordered eating, yet the evidence base is largely cross-sectional and limited to samples in certain Western countries. Furthermore, it is not clear whether these factors contribute to the prediction of eating disturbances independent of conceptually related risk factors emphasized within other sociocultural accounts. In this prospective study, body surveillance, body shame, and features of complementary sociocultural models (i.e., perceived appearance pressure from mass media and close interpersonal networks, appearance social comparisons, negative affect, body dissatisfaction) were assessed as risk factors for and concomitants of eating disturbances over time. University-age, mainland Chinese women (n = 2144) and men (n = 1017) completed validated measures of eating-disorder pathology and hypothesized risk factors at baseline (T1) and 1-year follow-up (T2). Among women, elevations on T1 measures of sociocultural-model features predicted more T2 eating disturbances, independent of T1 disturbances. After controlling for other T1 predictors, body surveillance and shame made modest unique contributions to the model. Finally, heightened T2 body dissatisfaction, media, and interpersonal appearance pressure, negative affect, and body shame predicted concomitant increases in T2 eating concerns. For men, T1 features of sociocultural accounts (negative affect, body dissatisfaction) but not OBC predicted T2 eating disturbances, along with attendant elevations in T2 negative affect, interpersonal appearance pressure, and body shame. Implications are discussed for theory and intervention that target disordered eating. (c) 2015 APA, all rights reserved).
Evaluation of fetal anthropometric measures to predict the risk for shoulder dystocia.
Burkhardt, T; Schmidt, M; Kurmanavicius, J; Zimmermann, R; Schäffer, L
2014-01-01
To evaluate the quality of anthropometric measures to improve the prediction of shoulder dystocia by combining different sonographic biometric parameters. This was a retrospective cohort study of 12,794 vaginal deliveries with complete sonographic biometry data obtained within 7 days before delivery. Receiver-operating characteristics (ROC) curves of various combinations of the biometric parameters, namely, biparietal diameter (BPD), occipitofrontal diameter (OFD), head circumference, abdominal diameter (AD), abdominal circumference (AC) and femur length were analyzed. The influences of independent risk factors were calculated and their combination used in a predictive model. The incidence of shoulder dystocia was 1.14%. Different combinations of sonographic parameters showed comparable ROC curves without advantage for a particular combination. The difference between AD and BPD (AD - BPD) (area under the curve (AUC) = 0.704) revealed a significant increase in risk (odds ratio (OR) 7.6 (95% CI 4.2-13.9), sensitivity 8.2%, specificity 98.8%) at a suggested cut-off ≥ 2.6 cm. However, the positive predictive value (PPV) was low (7.5%). The AC as a single parameter (AUC = 0.732) with a cut-off ≥ 35 cm performed worse (OR 4.6 (95% CI 3.3-6.5), PPV 2.6%). BPD/OFD (a surrogate for fetal cranial shape) was not significantly different between those with and those without shoulder dystocia. The combination of estimated fetal weight, maternal diabetes, gender and AD - BPD provided a reasonable estimate of the individual risk. Sonographic fetal anthropometric measures appear not to be a useful tool to screen for the risk of shoulder dystocia due to a low PPV. However, AD - BPD appears to be a relevant risk factor. While risk stratification including different known risk factors may aid in counseling, shoulder dystocia cannot effectively be predicted. Copyright © 2013 ISUOG. Published by John Wiley & Sons Ltd.
Predictive factors for red blood cell transfusion in children undergoing noncomplex cardiac surgery.
Mulaj, Muj; Faraoni, David; Willems, Ariane; Sanchez Torres, Cristel; Van der Linden, Philippe
2014-08-01
Red blood cell (RBC) transfusion is frequently required in pediatric cardiac surgery and is associated with altered outcome and increased costs. Determining which factors predict transfusion in this context will enable clinicians to adopt strategies that will reduce the risk of RBC transfusion. This study aimed to assess predictive factors associated with RBC transfusion in children undergoing low-risk cardiac surgery with cardiopulmonary bypass (CPB). Children undergoing surgery to repair ventricular septal defect or atrioventricular septal defect from 2006 to 2011 were included in this retrospective study. Demography, preoperative laboratory testing, intraoperative data, and RBC transfusion were reviewed. Univariate and multivariate logistic regression analysis were used to define factors that were able to predict RBC transfusion. Then, we employed receiver operating characteristic analysis to design a predictive score. Among the 334 children included, 261 (78%) were transfused. Age (<18 months), priming volume of the CPB (>43 mL/kg), type of oxygenator used, minimal temperature reached during CPB (<32°C), and preoperative hematocrit (<34%) were independently associated with RBC transfusion in the studied population. A predictive score 2 or greater was the best predictor of RBC transfusion. The present study identified several factors that were significantly associated with perioperative RBC transfusion. Based on these factors, we designed a predictive score that can be used to develop a patient-based blood management program with the aim of reducing the incidence of RBC transfusion. Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
Tzoulaki, Ioanna; Murray, Gordon D; Lee, Amanda J; Rumley, Ann; Lowe, Gordon D O; Fowkes, F Gerald R
2007-04-24
The aim of our present study was to compare the association of a wide range of 17 biomarkers of inflammation, hemostasis, and blood rheology with incident heart disease and stroke after accounting for an indicator of subclinical atherosclerotic disease and traditional risk factors and also to determine their incremental predictive ability. We used data from the Edinburgh Artery Study, a population cohort study started in 1987 that comprised 1592 men and women aged 55 to 74 years. Subjects were followed for a mean of 17 years, and 416 of them suffered at least 1 cardiovascular event. In analyses adjusted for cardiovascular risk factors and history of cardiovascular disease (CVD): C-reactive protein, interleukin-6, fibrinogen, fibrin D-dimer, tissue plasminogen activator (t-PA), leukocyte elastase, and lipoprotein(a) (all P<0.01), as well as von Willebrand factor and plasma viscosity (both P<0.05), had significant hazard ratios for incident CVD. Further adjustment for a measure of subclinical atherosclerosis (ankle brachial index) had little impact on these associations. The hazard ratios (95% CI) for incident CVD between top and bottom tertiles in the latter analysis were 1.78 (1.30 to 2.45) for C-reactive protein, 1.85 (1.33 to 2.58) for interleukin-6, and 1.76 (1.35 to 2.31) for fibrinogen. Single biomarkers provided little additional discrimination of incident CVD to that obtained from cardiovascular risk factors and the ankle brachial index. An incremental score of multiple markers [interleukin-6, t-PA, intercellular adhesion molecule 1, and lipoprotein(a)] provided some added discrimination. Several "novel" risk factors predicted CVD after adjustments for conventional risk factors and also for a measure of asymptomatic disease. However, their incremental predictive ability was modest and their clinical utility remains uncertain.
Cardiovascular risk-factor knowledge and risk perception among HIV-infected adults.
Cioe, Patricia A; Crawford, Sybil L; Stein, Michael D
2014-01-01
Cardiovascular disease (CVD) has emerged as a major cause of morbidity and mortality in HIV-infected adults. Research in noninfected populations has suggested that knowledge of CVD risk factors significantly influences perceptions of risk. This cross-sectional study describes CVD risk factor knowledge and risk perception in HIV-infected adults. We recruited 130 HIV-infected adults (mean age = 48 years, 62% male, 56% current smokers, mean years since HIV diagnosis, 14.7). The mean CVD risk factor knowledge score was fairly high. However, controlling for age, CVD risk factor knowledge was not predictive of perceived risk [F(1, 117) = 0.13, p > .05]. Estimated risk and perceived risk were weakly but significantly correlated; r (126) = .24, p = .01. HIV-infected adults are at increased risk for CVD. Despite having adequate risk-factor knowledge, CVD risk perception was inaccurate. Improving risk perception and developing CVD risk reduction interventions for this population are imperative. Copyright © 2014 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.
Leslie, William D; Lix, Lisa M
2011-03-01
The World Health Organization (WHO) Fracture Risk Assessment Tool (FRAX) computes 10-year probability of major osteoporotic fracture from multiple risk factors, including femoral neck (FN) T-scores. Lumbar spine (LS) measurements are not currently part of the FRAX formulation but are used widely in clinical practice, and this creates confusion when there is spine-hip discordance. Our objective was to develop a hybrid 10-year absolute fracture risk assessment system in which nonvertebral (NV) fracture risk was assessed from the FN and clinical vertebral (V) fracture risk was assessed from the LS. We identified 37,032 women age 45 years and older undergoing baseline FN and LS dual-energy X-ray absorptiometry (DXA; 1990-2005) from a population database that contains all clinical DXA results for the Province of Manitoba, Canada. Results were linked to longitudinal health service records for physician billings and hospitalizations to identify nontrauma vertebral and nonvertebral fracture codes after bone mineral density (BMD) testing. The population was randomly divided into equal-sized derivation and validation cohorts. Using the derivation cohort, three fracture risk prediction systems were created from Cox proportional hazards models (adjusted for age and multiple FRAX risk factors): FN to predict combined all fractures, FN to predict nonvertebral fractures, and LS to predict vertebral (without nonvertebral) fractures. The hybrid system was the sum of nonvertebral risk from the FN model and vertebral risk from the LS model. The FN and hybrid systems were both strongly predictive of overall fracture risk (p < .001). In the validation cohort, ROC analysis showed marginally better performance of the hybrid system versus the FN system for overall fracture prediction (p = .24) and significantly better performance for vertebral fracture prediction (p < .001). In a discordance subgroup with FN and LS T-score differences greater than 1 SD, there was a significant improvement in overall fracture prediction with the hybrid method (p = .025). Risk reclassification under the hybrid system showed better alignment with observed fracture risk, with 6.4% of the women reclassified to a different risk category. In conclusion, a hybrid 10-year absolute fracture risk assessment system based on combining FN and LS information is feasible. The improvement in fracture risk prediction is small but supports clinical interest in a system that integrates LS in fracture risk assessment. Copyright © 2011 American Society for Bone and Mineral Research.
Predictive accuracy of combined genetic and environmental risk scores.
Dudbridge, Frank; Pashayan, Nora; Yang, Jian
2018-02-01
The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. © 2017 WILEY PERIODICALS, INC.
Predictive accuracy of combined genetic and environmental risk scores
Pashayan, Nora; Yang, Jian
2017-01-01
ABSTRACT The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. PMID:29178508
Norlin, D; Broberg, M
2013-06-01
Research on parents of children with intellectual disability (ID) has identified a range of risk and protective factors for parental well-being. In family research, the association between marital quality and depression is a vital field of investigation. Still little research has addressed how aspects of the couple relationship affect the adaptation of parents of children with ID. The present study examined predictive links between couple relationship factors (marital quality and coparenting quality) and individual well-being. Data were obtained through self-report questionnaires completed by parents of children with ID (mothers, n = 58; and fathers, n = 46) and control children (mothers, n = 178; and fathers, n = 141). To test the hypothesis that couple relationship factors predicted individual well-being, multiple regression analyses were performed controlling for the following risk factors identified by previous research: child self-injury/stereotypic behaviour, parenting stress, and economic risk. Marital quality predicted concurrent well-being, and coparenting quality predicted prospective well-being. Mothers of children with ID reported lower well-being than other parents. There is a continued need for investigation of the details of the links between couple relationship and individual well-being in parents of children with ID. Couple relationship factors should be given consideration in clinical interventions. © 2012 The Authors. Journal of Intellectual Disability Research © 2012 John Wiley & Sons Ltd, MENCAP & IASSID.
Lehmann, Nils; Erbel, Raimund; Mahabadi, Amir A; Rauwolf, Michael; Möhlenkamp, Stefan; Moebus, Susanne; Kälsch, Hagen; Budde, Thomas; Schmermund, Axel; Stang, Andreas; Führer-Sakel, Dagmar; Weimar, Christian; Roggenbuck, Ulla; Dragano, Nico; Jöckel, Karl-Heinz
2018-02-13
Computed tomography (CT) allows estimation of coronary artery calcium (CAC) progression. We evaluated several progression algorithms in our unselected, population-based cohort for risk prediction of coronary and cardiovascular events. In 3281 participants (45-74 years of age), free from cardiovascular disease until the second visit, risk factors, and CTs at baseline (b) and after a mean of 5.1 years (5y) were measured. Hard coronary and cardiovascular events, and total cardiovascular events including revascularization, as well, were recorded during a follow-up time of 7.8±2.2 years after the second CT. The added predictive value of 10 CAC progression algorithms on top of risk factors including baseline CAC was evaluated by using survival analysis, C-statistics, net reclassification improvement, and integrated discrimination index. A subgroup analysis of risk in CAC categories was performed. We observed 85 (2.6%) hard coronary, 161 (4.9%) hard cardiovascular, and 241 (7.3%) total cardiovascular events. Absolute CAC progression was higher with versus without subsequent coronary events (median, 115 [Q1-Q3, 23-360] versus 8 [0-83], P <0.0001; similar for hard/total cardiovascular events). Some progression algorithms added to the predictive value of baseline CT and risk assessment in terms of C-statistic or integrated discrimination index, especially for total cardiovascular events. However, CAC progression did not improve models including CAC 5y and 5-year risk factors. An excellent prognosis was found for 921 participants with double-zero CAC b =CAC 5y =0 (10-year coronary and hard/total cardiovascular risk: 1.4%, 2.0%, and 2.8%), which was for participants with incident CAC 1.8%, 3.8%, and 6.6%, respectively. When CAC b progressed from 1 to 399 to CAC 5y ≥400, coronary and total cardiovascular risk were nearly 2-fold in comparison with subjects who remained below CAC 5y =400. Participants with CAC b ≥400 had high rates of hard coronary and hard/total cardiovascular events (10-year risk: 12.0%, 13.5%, and 30.9%, respectively). CAC progression is associated with coronary and cardiovascular event rates, but adds only weakly to risk prediction. What counts is the most recent CAC value and risk factor assessment. Therefore, a repeat scan >5 years after the first scan may be of additional value, except when a double-zero CT scan is present or when the subjects are already at high risk. © 2017 The Authors.
Return to Work After Lumbar Microdiscectomy - Personalizing Approach Through Predictive Modeling.
Papić, Monika; Brdar, Sanja; Papić, Vladimir; Lončar-Turukalo, Tatjana
2016-01-01
Lumbar disc herniation (LDH) is the most common disease among working population requiring surgical intervention. This study aims to predict the return to work after operative treatment of LDH based on the observational study including 153 patients. The classification problem was approached using decision trees (DT), support vector machines (SVM) and multilayer perception (MLP) combined with RELIEF algorithm for feature selection. MLP provided best recall of 0.86 for the class of patients not returning to work, which combined with the selected features enables early identification and personalized targeted interventions towards subjects at risk of prolonged disability. The predictive modeling indicated at the most decisive risk factors in prolongation of work absence: psychosocial factors, mobility of the spine and structural changes of facet joints and professional factors including standing, sitting and microclimate.
Assessment of soil erosion risk in Komering watershed, South Sumatera, using SWAT model
NASA Astrophysics Data System (ADS)
Salsabilla, A.; Kusratmoko, E.
2017-07-01
Changes in land use watershed led to environmental degradation. Estimated loss of soil erosion is often difficult due to some factors such as topography, land use, climate and human activities. This study aims to predict soil erosion hazard and sediment yield using the Soil and Water Assessment Tools (SWAT) hydrological model. The SWAT was chosen because it can simulate the model with limited data. The study area is Komering watershed (806,001 Ha) in South Sumatera Province. There are two factors land management intervention: 1) land with agriculture, and 2) land with cultivation. These factors selected in accordance with the regulations of spatial plan area. Application of the SWAT demonstrated that the model can predict surface runoff, soil erosion loss and sediment yield. The erosion risk for each watershed can be classified and predicted its changes based on the scenarios which arranged. In this paper, we also discussed the relationship between the distribution of erosion risk and watershed's characteristics in a spatial perspective.
Kim, Ji Soo; Choi, Jeong Sil
2016-09-01
The purpose of this study was to identify factors predicting clinical nurses' willingness to care for Ebola virus disease (EVD)-infected patients. Data were collected from 179 nurses employed at 10 hospitals in Korea using self-reporting questionnaires. Only 26.8% of the participants were willing to care for EVD-infected patients. Factors predicting their willingness to provide care were their belief in public service, risk perception, and age. Nurses' willingness to provide care was high when their belief in public service was high, low when their risk perception was high, and low as their age increased. In order to strengthen nurses' willingness to care for EVD-infected patients, education that targets the enhancement of belief in public service should be included in nurse training. Efforts should be directed toward lowering EVD risk perception and developing systematic responses through government-led organized support. © 2015 Wiley Publishing Asia Pty Ltd.
Buchmann, Arlette F; Blomeyer, Dorothea; Laucht, Manfred
2012-01-01
Suicidal behaviors are prevalent among young people. Numerous risk factors have been implicated in their development. In the framework of the longitudinal Mannheim Study of Children at Risk, 311 young adults (143 males, 168 females) aged 19-23 years were investigated in order 1) to determine the significance of different risk factors during development in predicting suicidal behaviors in young adulthood, 2) to identify potential risk factors discriminating between suicidal ideation and suicide attempts, and 3) to examine whether the effect of early risk factors was mediated by later occurring predictors. Young adults with suicidal behaviors displayed a number of abnormalities during development, including high load of early family adversity, suicidal ideation and psychiatric problems in childhood and adolescence, as well as low self esteem, poor school functioning, higher levels of novelty seeking, and enhanced affiliations with deviant peers in adolescence. Independent contributions to predicting suicidal behaviors in young adults were provided by early family adversity, suicidal ideation during childhood and adolescence, and low self esteem (with regard to suicidal ideation) and novelty seeking (with regard to suicide attempt), respectively. The impact of early adversity was mediated by child and adolescent externalizing disorders and low self esteem in adolescence. Possible implications of these findings for the prevention and treatment of suicidal behaviors are discussed.
Modifiable pathways in Alzheimer's disease: Mendelian randomisation analysis.
Larsson, Susanna C; Traylor, Matthew; Malik, Rainer; Dichgans, Martin; Burgess, Stephen; Markus, Hugh S
2017-12-06
To determine which potentially modifiable risk factors, including socioeconomic, lifestyle/dietary, cardiometabolic, and inflammatory factors, are associated with Alzheimer's disease. Mendelian randomisation study using genetic variants associated with the modifiable risk factors as instrumental variables. International Genomics of Alzheimer's Project. 17 008 cases of Alzheimer's disease and 37 154 controls. Odds ratio of Alzheimer's per genetically predicted increase in each modifiable risk factor estimated with Mendelian randomisation analysis. This study included analyses of 24 potentially modifiable risk factors. A Bonferroni corrected threshold of P=0.002 was considered to be significant, and P<0.05 was considered suggestive of evidence for a potential association. Genetically predicted educational attainment was significantly associated with Alzheimer's. The odds ratios were 0.89 (95% confidence interval 0.84 to 0.93; P=2.4×10 -6 ) per year of education completed and 0.74 (0.63 to 0.86; P=8.0×10 -5 ) per unit increase in log odds of having completed college/university. The correlated trait intelligence had a suggestive association with Alzheimer's (per genetically predicted 1 SD higher intelligence: 0.73, 0.57 to 0.93; P=0.01). There was suggestive evidence for potential associations between genetically predicted higher quantity of smoking (per 10 cigarettes a day: 0.69, 0.49 to 0.99; P=0.04) and 25-hydroxyvitamin D concentrations (per 20% higher levels: 0.92, 0.85 to 0.98; P=0.01) and lower odds of Alzheimer's and between higher coffee consumption (per one cup a day: 1.26, 1.05 to 1.51; P=0.01) and higher odds of Alzheimer's. Genetically predicted alcohol consumption, serum folate, serum vitamin B 12 , homocysteine, cardiometabolic factors, and C reactive protein were not associated with Alzheimer's disease. These results provide support that higher educational attainment is associated with a reduced risk of Alzheimer's disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Yashi, Masahiro; Nukui, Akinori; Tokura, Yuumi; Takei, Kohei; Suzuki, Issei; Sakamoto, Kazumasa; Yuki, Hideo; Kambara, Tsunehito; Betsunoh, Hironori; Abe, Hideyuki; Fukabori, Yoshitatsu; Nakazato, Yoshimasa; Kaji, Yasushi; Kamai, Takao
2017-06-23
Many urologic surgeons refer to biopsy core details for decision making in cases of localized prostate cancer (PCa) to determine whether an extended resection and/or lymph node dissection should be performed. Furthermore, recent reports emphasize the predictive value of prostate-specific antigen density (PSAD) for further risk stratification, not only for low-risk PCa, but also for intermediate- and high-risk PCa. This study focused on these parameters and compared respective predictive impact on oncologic outcomes in Japanese PCa patients. Two-hundred and fifty patients with intermediate- and high-risk PCa according to the National Comprehensive Cancer Network (NCCN) classification, that underwent robot-assisted radical prostatectomy at a single institution, and with observation periods of longer than 6 months were enrolled. None of the patients received hormonal treatments including antiandrogens, luteinizing hormone-releasing hormone analogues, or 5-alpha reductase inhibitors preoperatively. PSAD and biopsy core details, including the percentage of positive cores and the maximum percentage of cancer extent in each positive core, were analyzed in association with unfavorable pathologic results of prostatectomy specimens, and further with biochemical recurrence. The cut-off values of potential predictive factors were set through receiver-operating characteristic curve analyses. In the entire cohort, a higher PSAD, the percentage of positive cores, and maximum percentage of cancer extent in each positive core were independently associated with advanced tumor stage ≥ pT3 and an increased index tumor volume > 0.718 ml. NCCN classification showed an association with a tumor stage ≥ pT3 and a Gleason score ≥8, and the attribution of biochemical recurrence was also sustained. In each NCCN risk group, these preoperative factors showed various associations with unfavorable pathological results. In the intermediate-risk group, the percentage of positive cores showed an independent predictive value for biochemical recurrence. In the high-risk group, PSAD showed an independent predictive value. PSAD and biopsy core details have different performance characteristics for the prediction of oncologic outcomes in each NCCN risk group. Despite the need for further confirmation of the results with a larger cohort and longer observation, these factors are important as preoperative predictors in addition to the NCCN classification for a urologic surgeon to choose a surgical strategy.
Eating in the absence of hunger during childhood predicts self-reported binge eating in adolescence.
Balantekin, Katherine N; Birch, Leann L; Savage, Jennifer S
2017-01-01
The objectives of the current study were to examine whether eating in the absence of hunger (EAH) at age 7 predicted reports of self-reported binge eating at age 15 and to identify factors among girls with high-EAH that moderated risk of later binge eating. Subjects included 158 girls assessed at age 7 and age 15. Logistic regression was used to predict binge eating at age 15 from calories consumed during EAH at age 7. A series of logistic regressions were used to examine the odds of reporting binge eating given levels of risk factors (e.g., anxiety) among those with high-EAH in childhood. Girls' EAH intake predicted reports of binge eating at age 15; after adjusting for age 7 BMI, for each additional 100kcal consumed, girls were 1.7 times more likely to report binge eating in adolescence. Among those with high-EAH, BMI, anxiety, depression, dietary restraint, emotional disinhibition, and body dissatisfaction all predicted binge eating. EAH during childhood predicted reports of binge eating during adolescence; girls with elevated BMI, negative affect, and maladaptive eating- and weight-related cognitions were at increased risk. High-EAH in childhood may be useful for indicating those at risk for developing binge eating. Copyright © 2016 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Flouri, Eirini
2007-01-01
Using longitudinal data from the 1970 British Cohort Study, this study explored conditions under which the effects of risk factors for low educational attainment might be moderated. Two different risk factors, hyperactivity and maternal authoritarian parenting attitudes, were studied. The results showed that on the whole these two risk factors…
USDA-ARS?s Scientific Manuscript database
BACKGROUND: Cross-sectional data indicate that central adiposity is associated with cardiovascular disease risk, independent of total adiposity. The use of longitudinal data to investigate the relation between changes in fat distribution and the emergence of risk factors is limited. OBJECTIVE: We ...
Prevalence and predictors of verbal aggression in a secure mental health service: Use of the HCR-20.
Gunenc, Cevher; O'Shea, Laura E; Dickens, Geoffrey L
2015-08-01
Despite evidence about the negative effects of verbal aggression in mental health wards there is little research about its prevalence or about the factors that predict the behaviour among inpatients. This study aimed to determine the prevalence of verbal aggression in a secure mental health service, and to examine the relationship of verbal aggression with risk factors for aggression in the risk assessment tool HCR-20 in order to establish whether, and with which factors, the behaviour can be predicted. Verbal aggression was measured using the Overt Aggression Scale (OAS) over a 3-month period across a heterogeneous patient group (n = 613). Over half the patients (n = 341, 56%) engaged in 1594 incidents of verbal aggression. The HCR-20 total, clinical, and risk management subscale scores predicted verbal aggression, though effect sizes were not large. Item-outcome analysis revealed that impulsivity, negative attitudes, and non-compliance with medication were the best predictors of verbal aggression and, therefore, should be targeted for intervention. There are key synergies between factors predicting verbal aggression and the core mental health nursing role. Nurses, therefore, are in a prime position to develop and implement interventions that may reduce verbal aggression in mental health inpatients. © 2015 Australian College of Mental Health Nurses Inc.
Prostate cancer: predicting high-risk prostate cancer-a novel stratification tool.
Buck, Jessica; Chughtai, Bilal
2014-05-01
Currently, numerous systems exist for the identification of high-risk prostate cancer, but few of these systems can guide treatment strategies. A new stratification tool that uses common diagnostic factors can help to predict outcomes after radical prostatectomy. The tool aids physicians in the identification of appropriate candidates for aggressive, local treatment.
Predicting the Risk of Breakthrough Urinary Tract Infections: Primary Vesicoureteral Reflux.
Hidas, Guy; Billimek, John; Nam, Alexander; Soltani, Tandis; Kelly, Maryellen S; Selby, Blake; Dorgalli, Crystal; Wehbi, Elias; McAleer, Irene; McLorie, Gordon; Greenfield, Sheldon; Kaplan, Sherrie H; Khoury, Antoine E
2015-11-01
We constructed a risk prediction instrument stratifying patients with primary vesicoureteral reflux into groups according to their 2-year probability of breakthrough urinary tract infection. Demographic and clinical information was retrospectively collected in children diagnosed with primary vesicoureteral reflux and followed for 2 years. Bivariate and binary logistic regression analyses were performed to identify factors associated with breakthrough urinary tract infection. The final regression model was used to compute an estimation of the 2-year probability of breakthrough urinary tract infection for each subject. Accuracy of the binary classifier for breakthrough urinary tract infection was evaluated using receiver operator curve analysis. Three distinct risk groups were identified. The model was then validated in a prospective cohort. A total of 252 bivariate analyses showed that high grade (IV or V) vesicoureteral reflux (OR 9.4, 95% CI 3.8-23.5, p <0.001), presentation after urinary tract infection (OR 5.3, 95% CI 1.1-24.7, p = 0.034) and female gender (OR 2.6, 95% CI 0.097-7.11, p <0.054) were important risk factors for breakthrough urinary tract infection. Subgroup analysis revealed bladder and bowel dysfunction was a significant risk factor more pronounced in low grade (I to III) vesicoureteral reflux (OR 2.8, p = 0.018). The estimation model was applied for prospective validation, which demonstrated predicted vs actual 2-year breakthrough urinary tract infection rates of 19% vs 21%. Stratifying the patients into 3 risk groups based on parameters in the risk model showed 2-year risk for breakthrough urinary tract infection was 8.6%, 26.0% and 62.5% in the low, intermediate and high risk groups, respectively. This proposed risk stratification and probability model allows prediction of 2-year risk of patient breakthrough urinary tract infection to better inform parents of possible outcomes and treatment strategies. Copyright © 2015 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Busseri, Michael A; Willoughby, Teena; Chalmers, Heather; Bogaert, Anthony F
2008-01-01
On the basis of a large-scale survey of high-school youth, the authors compared adolescents reporting exclusively heterosexual, mostly heterosexual, bisexual, and predominately same-sex attraction based on high-risk involvement across a range of risk behaviors. Bisexual and same-sex attracted groups were characterized by heightened high-risk involvement relative to the other two groups. Mediation analysis was used to determine whether these group disparities were explained by a set of normative predictive factors spanning multiple life domains. Differences among a combined exclusively/mostly heterosexual attraction group and both the bisexual and same-sex attraction groups were attenuated (66% and 50%, respectively) after incorporating the hypothesized intervening predictive factors, providing evidence of partial mediation. Primary mediators included intrapersonal (attitudes toward risk-taking; academic orientation), interpersonal (peer victimization; parental relationships; unstructured activities), and environmental (substance availability) factors. Mediation results were consistent across participant age and sex. Implications, limitations, and directions for future research are discussed. Copyright (c) 2008 APA.
Sudden cardiac death: epidemiology and risk factors
Adabag, A. Selcuk; Luepker, Russell V.; Roger, Véronique L.; Gersh, Bernard J.
2016-01-01
Sudden cardiac death (SCD) is an important public-health problem with multiple etiologies, risk factors, and changing temporal trends. Substantial progress has been made over the past few decades in identifying markers that confer increased SCD risk at the population level. However, the quest for predicting the high-risk individual who could be a candidate for an implantable cardioverter-defibrillator, or other therapy, continues. In this article, we review the incidence, temporal trends, and triggers of SCD, and its demographic, clinical, and genetic risk factors. We also discuss the available evidence supporting the use of public-access defibrillators. PMID:20142817
Takahashi, Paul Y; Heien, Herbert C; Sangaralingham, Lindsey R; Shah, Nilay D; Naessens, James M
2016-07-01
With the advent of healthcare payment reform, identifying high-risk populations has become more important to providers. Existing risk-prediction models often focus on chronic conditions. This study sought to better understand other factors to improve identification of the highest risk population. A retrospective cohort study of a paneled primary care population utilizing 2010 data to calibrate a risk prediction model of hospital and emergency department (ED) use in 2011. Data were randomly split into development and validation data sets. We compared the enhanced model containing the additional risk predictors with the Minnesota medical tiering model. The study was conducted in the primary care practice of an integrated delivery system at an academic medical center in Rochester, Minnesota. The study focus was primary care medical home patients in 2010 and 2011 (n = 84,752), with the primary outcome of subsequent hospitalization or ED visit. A total of 42,384 individuals derived the enhanced risk-prediction model and 42,368 individuals validated the model. Predictors included Adjusted Clinical Groups-based Minnesota medical tiering, patient demographics, insurance status, and prior year healthcare utilization. Additional variables included specific mental and medical conditions, use of high-risk medications, and body mass index. The area under the curve in the enhanced model was 0.705 (95% CI, 0.698-0.712) compared with 0.662 (95% CI, 0.656-0.669) in the Minnesota medical tiering-only model. New high-risk patients in the enhanced model were more likely to have lack of health insurance, presence of Medicaid, diagnosed depression, and prior ED utilization. An enhanced model including additional healthcare-related factors improved the prediction of risk of hospitalization or ED visit.
Wild Fire Risk Map in the Eastern Steppe of Mongolia Using Spatial Multi-Criteria Analysis
NASA Astrophysics Data System (ADS)
Nasanbat, Elbegjargal; Lkhamjav, Ochirkhuyag
2016-06-01
Grassland fire is a cause of major disturbance to ecosystems and economies throughout the world. This paper investigated to identify risk zone of wildfire distributions on the Eastern Steppe of Mongolia. The study selected variables for wildfire risk assessment using a combination of data collection, including Social Economic, Climate, Geographic Information Systems, Remotely sensed imagery, and statistical yearbook information. Moreover, an evaluation of the result is used field validation data and assessment. The data evaluation resulted divided by main three group factors Environmental, Social Economic factor, Climate factor and Fire information factor into eleven input variables, which were classified into five categories by risk levels important criteria and ranks. All of the explanatory variables were integrated into spatial a model and used to estimate the wildfire risk index. Within the index, five categories were created, based on spatial statistics, to adequately assess respective fire risk: very high risk, high risk, moderate risk, low and very low. Approximately more than half, 68 percent of the study area was predicted accuracy to good within the very high, high risk and moderate risk zones. The percentages of actual fires in each fire risk zone were as follows: very high risk, 42 percent; high risk, 26 percent; moderate risk, 13 percent; low risk, 8 percent; and very low risk, 11 percent. The main overall accuracy to correct prediction from the model was 62 percent. The model and results could be support in spatial decision making support system processes and in preventative wildfire management strategies. Also it could be help to improve ecological and biodiversity conservation management.
Solomon, Daniel H.; Kremer, Joel; Curtis, Jeffrey R; Hochberg, Marc C.; Reed, George; Tsao, Peter; Farkouh, Michael E.; Setoguchi, Soko; Greenberg, Jeffrey D.
2010-01-01
Background Cardiovascular (CV) disease has a major impact on patients with rheumatoid arthritis (RA), however, the relative contributions of traditional CV risk factors and markers of RA severity are unclear. We examined the relative importance of traditional CV risk factors and RA markers in predicting CV events. Methods A prospective longitudinal cohort study was conducted in the setting of the CORRONA registry in the United States. Baseline data from subjects with RA enrolled in the CORRONA registry were examined to determine predictors of CV outcomes, including myocardial infarction (MI), stroke or transient ischemic attack (TIA). Possible predictors were of two types: traditional CV risk factors and markers of RA severity. The discriminatory value of these variables was assessed by calculating the area under the receiver operating characteristic curve (c-statistic) in logistic regression. We then assessed the incidence rate for CV events among subjects with an increasing number of traditional CV risk factors and/or RA severity markers. Results The cohort consisted of 10,156 patients with RA followed for a median of 22 months. We observed 76 primary CV events during follow-up for a composite event rate of 3.98 (95% CI 3.08 – 4.88) per 1,000 patient-years. The c-statistic improved from 0.57 for models with only CV risk factors to 0.67 for models with CV risk factors plus age and gender. The c-statistic improved further to 0.71 when markers of RA severity were also added. The incidence rate for CV events was 0 (95% CI 0 – 5.98) for persons without any CV risk factors or markers of RA severity, while in the group with two or more CV risk factors and 3 or more markers of RA severity the incidence was 7.47 (95% CI 4.21–10.73) per 1,000 person-years. Conclusions Traditional CV risk factors and markers of RA severity both contribute to models predicting CV events. Increasing numbers of both types of factors are associated with greater risk. PMID:20444756
Tsikouras, Panagiotis; Anastasopoulos, George; Maroulis, Vasileios; Bothou, Anastasia; Chalkidou, Anna; Deuteraiou, Dorelia; Anthoulaki, Xanthoula; Bourazan, Arzou Halil; Iatrakis, George; Zervoudis, Stefanos; Galazios, Georgios; Inagamova, Lola-Katerina; Csorba, Roland; Teichmann, Alexander-Tobias
2018-01-01
Objective: Preterm labor is one of the most significant obstetric problems associated with high rate of actual and long-term perinatal complications. Despite the creation of scoring systems, uterine activity monitoring, cervical ultrasound and several biochemical markers, the prediction and prevention of preterm labor is still a matter of concern. The aim of this study was to examine cervical findings for the prediction and the comparative use of Arabin pessary or cerclage for the prevention of preterm birth in asymptomatic women with high risk factors for preterm labor. Material and methods: The study group was composed of singleton pregnancies (spontaneously conceived) with high risk factors for preterm labor. Cervical length, dilatation of the internal cervical os and funneling, were estimated with transvaginal ultrasound during the first and the second trimesters of pregnancy. Results: Cervical funneling, during the second trimester of pregnancy, was the most significant factor for the prediction of preterm labor. The use of Arabin cervical pessary was found to be more effective than cerclage in the prolongation of pregnancy. Conclusion: In women at risk for preterm labor, the detection of cervical funneling in the second trimester of pregnancy may help to predict preterm labor and to apply the appropriate treatment for its prevention. Although the use of cervical pessary was found to be more effective than cerclage, more studies are needed to classify the effectiveness of different methods for such prevention. PMID:29670041
Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid
2018-05-12
Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.
Thomas, B S
1996-01-01
Gender differences in the ways a risk factor approach explains onset of using alcohol, tobacco and other drugs (ATOD), reported use of ATOD and adverse consequences from ATOD use were investigated by means of separate path analyses for male and female adolescents. A fully recursive model was specified in which alienation, trait anger, interaction anxiety and cognitive motivation for ATOD use comprised the first column variables which were used to predict earliness of onset. For the second step, column one variables plus onset were used to predict ATOD use. In the final step, column one variables plus onset and ATOD use were used to predict adverse consequences of ATOD use. An ex post facto design was used in surveying 796 high school students in a single Midwestern community. The data from this sample supported the predictive validity of the theoretical model. In addition to the expected indirect or mediated effects of the risk factors via onset of ATOD use on ATOD use and via onset and ATOD use on adverse consequences of ATOD use, there were direct effects of column on risk factors on both ATOD use and on adverse consequences of ATOD use for both males and females, lending support to the concept of multiple pathway risk factors. The three gender differences that emerged in the separate path analyses were entirely consistent with the gendered deviance model.
Uncertainty Considerations for Ballistic Limit Equations
NASA Technical Reports Server (NTRS)
Schonberg, W. P.; Evans, H. J.; Williamsen, J. E; Boyer, R. L.; Nakayama, G. S.
2005-01-01
The overall risk for any spacecraft system is typically determined using a Probabilistic Risk Assessment (PRA). A PRA determines the overall risk associated with a particular mission by factoring in all known risks to the spacecraft during its mission. The threat to mission and human life posed by the micro-meteoroid and orbital debris (MMOD) environment is one of the risks. NASA uses the BUMPER II program to provide point estimate predictions of MMOD risk for the Space Shuttle and the ISS. However, BUMPER II does not provide uncertainty bounds or confidence intervals for its predictions. In this paper, we present possible approaches through which uncertainty bounds can be developed for the various damage prediction and ballistic limit equations encoded within the Shuttle and Station versions of BUMPER II.
Wickramasinghe, Chanaka D; Ayers, Colby R; Das, Sandeep; de Lemos, James A; Willis, Benjamin L; Berry, Jarett D
2014-07-01
Fitness and traditional risk factors have well-known associations with cardiovascular disease (CVD) death in both short-term (10 years) and across the remaining lifespan. However, currently available short-term and long-term risk prediction tools do not incorporate measured fitness. We included 16 533 participants from the Cooper Center Longitudinal Study (CCLS) without prior CVD. Fitness was measured using the Balke protocol. Sex-specific fitness levels were derived from the Balke treadmill times and categorized into low, intermediate, and high fit according to age- and sex-specific treadmill times. Sex-specific 30-year risk estimates for CVD death adjusted for competing risk of non-CVD death were estimated using the cause-specific hazards model and included age, body mass index, systolic blood pressure, fitness, diabetes mellitus, total cholesterol, and smoking. During a median follow-up period of 28 years, there were 1123 CVD deaths. The 30-year risk estimates for CVD mortality derived from the cause-specific hazards model demonstrated overall good calibration (Nam-D'Agostino χ(2) [men, P=0.286; women, P=0.664] and discrimination (c statistic; men, 0.81 [0.80-0.82] and women, 0.86 [0.82-0.91]). Across all risk factor strata, the presence of low fitness was associated with a greater 30-year risk for CVD death. Fitness represents an important additional covariate in 30-year risk prediction functions that may serve as a useful tool in clinical practice. © 2014 American Heart Association, Inc.
Direct and indirect effects of biological factors on extinction risk in fossil bivalves
Harnik, Paul G.
2011-01-01
Biological factors, such as abundance and body size, may contribute directly to extinction risk and indirectly through their influence on other biological characteristics, such as geographic range size. Paleontological data can be used to explicitly test many of these hypothesized relationships, and general patterns revealed through analysis of the fossil record can help refine predictive models of extinction risk developed for extant species. Here, I use structural equation modeling to tease apart the contributions of three canonical predictors of extinction—abundance, body size, and geographic range size—to the duration of bivalve species in the early Cenozoic marine fossil record of the eastern United States. I find that geographic range size has a strong direct effect on extinction risk and that an apparent direct effect of abundance can be explained entirely by its covariation with geographic range. The influence of geographic range on extinction risk is manifest across three ecologically disparate bivalve clades. Body size also has strong direct effects on extinction risk but operates in opposing directions in different clades, and thus, it seems to be decoupled from extinction risk in bivalves as a whole. Although abundance does not directly predict extinction risk, I reveal weak indirect effects of both abundance and body size through their positive influence on geographic range size. Multivariate models that account for the pervasive covariation between biological factors and extinction are necessary for assessing causality in evolutionary processes and making informed predictions in applied conservation efforts. PMID:21808004
Direct and indirect effects of biological factors on extinction risk in fossil bivalves.
Harnik, Paul G
2011-08-16
Biological factors, such as abundance and body size, may contribute directly to extinction risk and indirectly through their influence on other biological characteristics, such as geographic range size. Paleontological data can be used to explicitly test many of these hypothesized relationships, and general patterns revealed through analysis of the fossil record can help refine predictive models of extinction risk developed for extant species. Here, I use structural equation modeling to tease apart the contributions of three canonical predictors of extinction--abundance, body size, and geographic range size--to the duration of bivalve species in the early Cenozoic marine fossil record of the eastern United States. I find that geographic range size has a strong direct effect on extinction risk and that an apparent direct effect of abundance can be explained entirely by its covariation with geographic range. The influence of geographic range on extinction risk is manifest across three ecologically disparate bivalve clades. Body size also has strong direct effects on extinction risk but operates in opposing directions in different clades, and thus, it seems to be decoupled from extinction risk in bivalves as a whole. Although abundance does not directly predict extinction risk, I reveal weak indirect effects of both abundance and body size through their positive influence on geographic range size. Multivariate models that account for the pervasive covariation between biological factors and extinction are necessary for assessing causality in evolutionary processes and making informed predictions in applied conservation efforts.
Hirani, Vasant; Naganathan, Vasi; Blyth, Fiona; Le Couteur, David G; Gnjidic, Danijela; Stanaway, Fiona F; Seibel, Markus J; Waite, Louise M; Handelsman, David J; Cumming, Robert G
2014-01-01
This study aims to identify the common risk factors for mortality in community-dwelling older men. A prospective population-based study was conducted with a median of 6.7 years of follow-up. Participants included 1705 men aged ≥70 years at baseline (2005-2007) living in the community in Sydney, Australia. Demographic information, lifestyle factors, health status, self-reported history of diseases, physical performance measures, blood pressure, height and weight, disability (activities of daily living (ADL) and instrumental ADLs, instrumental ADLs (IADLs)), cognitive status, depressive symptoms and blood analyte measures were considered. Cox regression analyses were conducted to model predictors delete time until of mortality. During follow-up, 461 men (27 %) died. Using Cox proportional hazards model, significant predictors of delete time to time to mortality included in the final model (p < 0.05) were older age, body mass index < 20 kg m(2), high white cell count, anaemia, low albumin, current smoking, history of cancer, history of myocardial infarction, history of congestive heart failure, depressive symptoms and ADL and IADL disability and impaired chair stands. We found that overweight and obesity and/or being a lifelong non-drinker of alcohol were protective against mortality. Compared to men with less than or equal to one risk factor, the hazard ratio in men with three risk factors was 2.5; with four risk factors, it was 4.0; with five risk factors, it was 4.9; and for six or more risk factors, it was 11.4, respectively. We have identified common risk factors that predict mortality that may be useful in making clinical decisions among older people living in the community. Our findings suggest that, in primary care, screening and management of multiple risk factors are important to consider for extending survival, rather than simply considering individual risk factors in isolation. Some of the "traditional" risk factors for mortality in a younger population, including high blood pressure, hypercholesterolaemia, overweight and obesity and diabetes, were not independent predictors of mortality in this population of older men.
Prognosis of Pregnant Women with One Abnormal Value on 75g OGTT.
Kozuma, Yutaka; Inoue, Shigeru; Horinouchi, Takashi; Shinagawa, Takaaki; Nakayama, Hitomi; Kawaguchi, Atsushi; Hori, Daizo; Kamura, Toshiharu; Yamada, Kentaro; Ushijima, Kimio
2015-01-01
The aim of this study was to identify risk factors to allow us to detect patients at high risk of requiring insulin therapy, among Japanese pregnant women with one abnormal value (OAV) on a 75-g oral glucose tolerance test (75-g OGTT). A total of 118 pregnant women with OAV on a previous 75-g OGTT between 1997 and 2010 were studied. We identified the factors which can predict patients at high risk of requiring insulin therapy among Japanese pregnant women with OAV, by comparing severe abnormal glucose tolerance (insulin treatment; n=17) with mild glucose tolerance patients (diet only; n=101). The following factors were examined; plasma level of glucose (PG) and immunoreactive insulin (IRI) at fasting, 0.5, 1 and 2 hours after loading glucose, insulinogenic index, homeostasis model assessment insulin resistance (HOMA-IR), insulin sensitivity index-composite (ISI composite), and HbA1c at the time of the 75-g OGTT. Univariate analysis showed a positive correlation between insulin therapy and 2-h PG value, 0.5-h and 1-h IRI values, AUC-IRI and insulinogenic index (p<0.05). Multivariate analysis showed that the PG 2-h value and insulinogenic index were independent predictive factors of insulin therapy. A 2-h PG ≥153 mg / dl and an insulinogenic index of <0.42 had a sensitivity of 81.8%, a specificity of 83.8%, a positive predictive value of 60.0% and a negative predictive value of 93.9% for the prediction of patients who required insulin therapy among pregnant women with OAV. These results suggest that a level of 2-h PG ≥153 mg/dl and an insulinogenic index of <0.42 on 75-g OGTT are predictive factors for insulin therapy in Japanese pregnant women with OAV.
Prediction of uncomplicated pregnancies in obese women: a prospective multicentre study.
Vieira, Matias C; White, Sara L; Patel, Nashita; Seed, Paul T; Briley, Annette L; Sandall, Jane; Welsh, Paul; Sattar, Naveed; Nelson, Scott M; Lawlor, Debbie A; Poston, Lucilla; Pasupathy, Dharmintra
2017-11-03
All obese pregnant women are considered at equal high risk with respect to complications in pregnancy and birth, and are commonly managed through resource-intensive care pathways. However, the identification of maternal characteristics associated with normal pregnancy outcomes could assist in the management of these pregnancies. The present study aims to identify the factors associated with uncomplicated pregnancy and birth in obese women, and to assess their predictive performance. Data form obese women (BMI ≥ 30 kg/m 2 ) with singleton pregnancies included in the UPBEAT trial were used in this analysis. Multivariable logistic regression was used to identify sociodemographic, clinical and biochemical factors at 15 +0 to 18 +6 weeks' gestation associated with uncomplicated pregnancy and birth, defined as delivery of a term live-born infant without antenatal or labour complications. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC). Internal validation and calibration were also performed. Women were divided into fifths of risk and pregnancy outcomes were compared between groups. Sensitivity, specificity, and positive and negative predictive values were calculated using the upper fifth as the positive screening group. Amongst 1409 participants (BMI 36.4, SD 4.8 kg/m 2 ), the prevalence of uncomplicated pregnancy and birth was 36% (505/1409). Multiparity and increased plasma adiponectin, maternal age, systolic blood pressure and HbA1c were independently associated with uncomplicated pregnancy and birth. These factors achieved an AUROC of 0.72 (0.68-0.76) and the model was well calibrated. Prevalence of gestational diabetes, preeclampsia and other hypertensive disorders, preterm birth, and postpartum haemorrhage decreased whereas spontaneous vaginal delivery increased across the fifths of increasing predicted risk of uncomplicated pregnancy and birth. Sensitivity, specificity, and positive and negative predictive values were 38%, 89%, 63% and 74%, respectively. A simpler model including clinical factors only (no biomarkers) achieved an AUROC of 0.68 (0.65-0.71), with sensitivity, specificity, and positive and negative predictive values of 31%, 86%, 56% and 69%, respectively. Clinical factors and biomarkers can be used to help stratify pregnancy and delivery risk amongst obese pregnant women. Further studies are needed to explore alternative pathways of care for obese women demonstrating different risk profiles for uncomplicated pregnancy and birth.
Risk Factors for Acute Kidney Injury in Severe Rhabdomyolysis
Rodríguez, Eva; Soler, María J.; Rap, Oana; Barrios, Clara; Orfila, María A.; Pascual, Julio
2013-01-01
Background Acute kidney injury (AKI) is a life-threatening complication of severe rhabdomyolysis. This study was conducted to assess risk factors for AKI and to develop a risk score for early prediction. Methods Retrospective observational cohort study with a 9-year follow-up, carried out in an acute-care teaching-affiliated hospital. A total of 126 patients with severe rhabdomyolysis defined as serum creatine kinase (CK) > 5,000 IU/L fulfilled the inclusion criteria. Univariate and logistic regression analyses were performed to determine risk factors for AKI. Based on the values obtained for each variable, a risk score and prognostic probabilities were estimated to establish the risk for developing AKI. Results The incidence of AKI was 58%. Death during hospitalization was significantly higher among patients with AKI, compared to patients without AKI (19.2% vs 3.6%, p = 0.008). The following variables were independently associated with AKI: peak CK (odds ratio [OR] 4.9, 95%CI 1.4-16.8), hypoalbuminemia (< 33 mg/dL, [OR 5.1, 95%CI 1.4-17-7]), metabolic acidosis (OR 5.3, 95%CI 1.4-20.3), and decreased prothrombin time (OR 4.4, 95% CI 1.3-14.5). A risk score for AKI was calculated for each patient, with an OR of 1.72 (95%CI 1.45-2.04). The discrimination value of the predictive model was established by means of a ROC curve, with the area under the curve of 0.871 (p<0.001). Conclusions The identification of independent factors associated with AKI and a risk score for early prediction of this complication in patients with severe rhabdomyolysis may be useful in clinical practice, particularly to implement early preventive measures. PMID:24367578
Predictions of space radiation fatality risk for exploration missions
NASA Astrophysics Data System (ADS)
Cucinotta, Francis A.; To, Khiet; Cacao, Eliedonna
2017-05-01
In this paper we describe revisions to the NASA Space Cancer Risk (NSCR) model focusing on updates to probability distribution functions (PDF) representing the uncertainties in the radiation quality factor (QF) model parameters and the dose and dose-rate reduction effectiveness factor (DDREF). We integrate recent heavy ion data on liver, colorectal, intestinal, lung, and Harderian gland tumors with other data from fission neutron experiments into the model analysis. In an earlier work we introduced distinct QFs for leukemia and solid cancer risk predictions, and here we consider liver cancer risks separately because of the higher RBE's reported in mouse experiments compared to other tumors types, and distinct risk factors for liver cancer for astronauts compared to the U.S. population. The revised model is used to make predictions of fatal cancer and circulatory disease risks for 1-year deep space and International Space Station (ISS) missions, and a 940 day Mars mission. We analyzed the contribution of the various model parameter uncertainties to the overall uncertainty, which shows that the uncertainties in relative biological effectiveness (RBE) factors at high LET due to statistical uncertainties and differences across tissue types and mouse strains are the dominant uncertainty. NASA's exposure limits are approached or exceeded for each mission scenario considered. Two main conclusions are made: 1) Reducing the current estimate of about a 3-fold uncertainty to a 2-fold or lower uncertainty will require much more expansive animal carcinogenesis studies in order to reduce statistical uncertainties and understand tissue, sex and genetic variations. 2) Alternative model assumptions such as non-targeted effects, increased tumor lethality and decreased latency at high LET, and non-cancer mortality risks from circulatory diseases could significantly increase risk estimates to several times higher than the NASA limits.
Predictors of formal home health care use in elderly patients after hospitalization.
Solomon, D H; Wagner, D R; Marenberg, M E; Acampora, D; Cooney, L M; Inouye, S K
1993-09-01
To prospectively study the incidence of and risk factors for home health care (HHC) use in a cohort of elderly medical and surgical patients discharged from acute care. Although HHC is commonly received by patients in this group, its predictors have not been well studied. Prospective cohort study. Medical and surgical wards at a university teaching hospital, followed by 23 Medicare-certified HHC agencies in the study catchment area. 226 medical and surgical patients aged 70 years and older immediately after discharge from acute care. HHC initiated within 14 days after hospital discharge, measured by direct review of HHC agency records. The incidence of HHC initiated within 2 weeks post-discharge was 75/226 (34%). The median duration of service was 30 days (range 3-483) with a median of 3 visits per week. Four independent predictors of HHC were identified through multivariate analysis: educational level < or = 12 years (relative risk (RR) 3.3; 95% confidence interval (CI) 1.6 to 6.6); less accessible social support (RR, 1.7; CI 0.9 to 3.1); impairment in at least one instrumental activity of daily living (RR, 1.9; CI, 1.0, 3.4); and prior HHC use (RR, 2.1; CI, 1.2 to 3.6). Risk strata were created by adding one point for each risk factor present: with 0-1 risk factors, 8% used HHC; with two risk factors, 28%; with three risk factors, 45%, with four risk factors, 76%. This trend was statistically significant (P < 0.001). HHC use is common among elderly patients after discharge from acute care. A simple predictive model based on four risk factors can be used on admission to predict HHC use. This model may be useful for discharge planning and health care utilization planning for the elderly population.
Hetherington-Rauth, Megan; Bea, Jennifer W; Lee, Vinson R; Blew, Robert M; Funk, Janet; Lohman, Timothy G; Going, Scott B
2017-02-23
Childhood overweight and obesity remains high, contributing to cardiometabolic risk factors at younger ages. It is unclear which measures of adiposity serve as the best proxies for identifying children at metabolic risk. This study assessed whether DXA-derived direct measures of adiposity are more strongly related to cardiometabolic risk factors in children than indirect measures. Anthropometric and DXA measures of adiposity and a comprehensive assessment of cardiometabolic risk factors were obtained in 288, 9-12 year old girls, most being of Hispanic ethnicity. Multiple regression models for each metabolic parameter were run against each adiposity measure while controlling for maturation and ethnicity. In addition, regression models including both indirect and direct measures were developed to assess whether using direct measures of adiposity could provide a better prediction of the cardiometabolic risk factors beyond that of using indirect measures alone. Measures of adiposity were significantly correlated with cardiometabolic risk factors (p < 0.05) except fasting glucose. After adjusting for maturation and ethnicity, indirect measures of adiposity accounted for 29-34% in HOMA-IR, 10-13% in TG, 14-17% in HDL-C, and 5-8% in LDL-C while direct measures accounted for 29-34% in HOMA-IR, 10-12% in TG, 13-16% in HDL-C, and 5-6% in LDL-C. The addition of direct measures of adiposity to indirect measures added significantly to the variance explained for HOMA-IR (p = 0.04). Anthropometric measures may perform as well as the more precise direct DXA-derived measures of adiposity for assessing most CVD risk factors in preadolescent girls. The use of DXA-derived adiposity measures together with indirect measures may be advantageous for predicting insulin resistance risk. NCT02654262 . Retrospectively registered 11 January 2016.